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704 commits

Author SHA1 Message Date
Research Assistant
946102bb9e bump: 1.5.8 -> 1.5.9 2026-05-19 15:44:52 +08:00
Research Assistant
cf4d929a24 fix(skill): add multi-intent collision rule to intent routing 2026-05-19 15:40:33 +08:00
Research Assistant
c21fc8db1e chore: remove temp test file 2026-05-19 15:28:43 +08:00
Research Assistant
8eb02ebdd4 feat(skill): add pre-flight checklist harness to SKILL.md and all molecules 2026-05-19 15:28:37 +08:00
Research Assistant
5ffcbde139 fix(skill): update stale workflow names for agent readability, remove commit convention debris and system write commands 2026-05-19 15:13:01 +08:00
Research Assistant
dfc80d0783 refactor(skill): remove legacy literature workflow entrypoints 2026-05-19 14:57:40 +08:00
Research Assistant
ee7e7306a4 test(skill): align downstream docs and setup with layered skill tree 2026-05-19 14:56:40 +08:00
Research Assistant
f02ec8b9aa refactor(skill): move chart-reading and method-card-template into atom layer 2026-05-19 14:55:06 +08:00
Research Assistant
9109fa3fa3 feat(skill): add capture-project-knowledge molecule and atoms 2026-05-19 14:54:05 +08:00
Research Assistant
6c458fb02a refactor(skill): migrate single-paper and deep-read molecules 2026-05-19 14:52:09 +08:00
Research Assistant
f533b6e6e3 refactor(skill): split discovery and evidence molecules 2026-05-19 14:51:07 +08:00
Research Assistant
7e03832291 feat(skill): add clarify-user-intent atom 2026-05-19 14:49:00 +08:00
Research Assistant
d9ab8fdbe7 refactor(skill): rewrite compound router for skill graph 2026-05-19 14:48:15 +08:00
Research Assistant
1fd4ae1f9f chore(skill): scaffold molecule and atom files 2026-05-19 14:46:53 +08:00
Research Assistant
819f51ed95 test(skill): add skill graph contract tests 2026-05-19 14:44:56 +08:00
Research Assistant
2912acbb5e refactor(skill): add atoms and molecules directories 2026-05-19 14:42:35 +08:00
Research Assistant
29a7e195c6 fix: add return type annotation to main() and indent=2 to early-exit json.dump calls 2026-05-19 14:41:06 +08:00
Research Assistant
948abb8280 refactor(bootstrap): avoid double read of dc_json, add explanatory comments
- Hoist plugin_data to function scope so capabilities section reuses
  the parsed dict instead of re-reading the file
- Add inline comment explaining semantic_enabled duplicates
  memory_layer.vector_search by design (runtime-health is authoritative)
- Add inline comment noting semantic_ready is a placeholder until a
  separate readiness probe is implemented
2026-05-19 14:39:42 +08:00
Research Assistant
261e92a788 feat(bootstrap): add capability probes to bootstrap output
Adds a capabilities block to the bootstrap JSON with runtime probes:
- rg: checks if ripgrep is available
- metadata_search: always True (vault config present)
- paper_context: always True
- semantic_enabled/semantic_ready: derived from plugin data.json

Test verifies the contract with an isolated tmp_path vault.
2026-05-19 14:36:05 +08:00
Research Assistant
34556ae6f2 docs: expand memory and embedding layer description in architecture 2026-05-19 02:07:53 +08:00
Research Assistant
eb987cf138 docs: add memory and embedding layer to architecture section 2026-05-19 01:59:05 +08:00
Research Assistant
8022b47f41 docs: restructure changelog - 1.5.7 as recovery, 1.5.8 as full release 2026-05-19 01:42:37 +08:00
Research Assistant
90fddfe967 chore: update versions.json for 1.5.6-1.5.8 2026-05-19 01:35:02 +08:00
Research Assistant
4b7ceefb5a chore: bump version to 1.5.8 2026-05-19 01:34:40 +08:00
Research Assistant
2c20138fd0 fix(plugin): finish orphan modal i18n for all remaining strings 2026-05-19 01:33:23 +08:00
Research Assistant
14e6872ec9 feat(plugin): i18n for orphan modal, label tweaks 2026-05-19 01:28:14 +08:00
Research Assistant
55b2e36025 fix(embed): detect model change in resume mode, report real chunk_count 2026-05-19 01:27:10 +08:00
Research Assistant
da92c1acc6 fix(manifest): remove 'Obsidian' from description (plugin review requirement) 2026-05-19 00:56:26 +08:00
Research Assistant
9a33c2f2fc docs: add CHANGELOG.md for 1.5.7 release 2026-05-19 00:52:33 +08:00
Research Assistant
90edb2e902 chore: bump version to 1.5.7 (1.5.6 version name taken on PyPI) 2026-05-19 00:48:59 +08:00
Research Assistant
263f43671d fix(publish): restore skip-existing, 1.5.6 already on PyPI 2026-05-19 00:48:14 +08:00
Research Assistant
b441b6694f fix(publish): disable skip-existing to force re-publish 2026-05-19 00:44:46 +08:00
Research Assistant
6f4481cc3e fix(publish): also trigger on tags without v prefix (e.g. 1.5.6) 2026-05-19 00:39:41 +08:00
Research Assistant
bd3608810d fix(release): also trigger on tags without v prefix (e.g. 1.5.6) 2026-05-19 00:37:42 +08:00
Research Assistant
1047c9851d chore: bump version to 1.5.6 2026-05-19 00:31:32 +08:00
Research Assistant
798e048a8d feat(sync): auto-detect orphan papers after sync, show modal in Obsidian
- prune.py: _enrich_orphan_preview() reads note frontmatter for metadata
- sync_service.py: always run dry-run prune, include in result
- sync.py: write sync-orphan-state.json for plugin consumption
- main.js: add checkOrphanState() + PaperForgeOrphanModal with select/toggle
- styles.css: orphan modal styles (list, tags, dimmed rows)
- cli.py: add --keys to prune command for targeted deletion
2026-05-19 00:31:19 +08:00
Research Assistant
a407520961 feat(prune): add interactive selection before --force delete 2026-05-18 23:28:04 +08:00
Research Assistant
528a8255bf chore: commit session work before hotfix switch 2026-05-18 22:47:30 +08:00
Research Assistant
e74f9139f3 perf(index): add export hash check to skip rebuild when BBT unchanged; remove redundant refresh_paper 2026-05-18 22:38:27 +08:00
Research Assistant
fe946d5ca4 chore: add phase timing to sync_service logging 2026-05-18 22:33:00 +08:00
Research Assistant
8fd1018cf2 feat(memory): show (fast) in sync output when hash matches 2026-05-18 22:29:53 +08:00
Research Assistant
48b564594c fix: remove undefined resolved_pdf ref, use pdf_attachments instead 2026-05-18 22:27:33 +08:00
Research Assistant
ad445a52d9 fix(sync): silent vector resume; nopdf resets to pending when PDF reappears 2026-05-18 22:26:48 +08:00
Research Assistant
0d3f3bfe98 fix(vector): get_collection no longer silently deletes collection on error; memory builder skips full rebuild when index hash matches 2026-05-18 22:18:23 +08:00
Research Assistant
945ad633de fix(sync): embed triggers async with DEVNULL output; memory rebuild runs once in commands layer; PDF errors are expected for missing Zotero files 2026-05-18 22:13:38 +08:00
Research Assistant
fad6eff83e fix(sync): memory/vector rebuilds are best-effort, not sync result; fix has_deep_reading_content import in asset_index.py 2026-05-18 22:09:42 +08:00
Research Assistant
febaacbcd4 chore: bump version to 1.5.6rc5 2026-05-18 22:00:58 +08:00
Research Assistant
e094457a67 style: fix lint issues (F541 f-strings, B007 unused var, F841 unused var) 2026-05-18 22:00:10 +08:00
Research Assistant
24f72e7d91 test(prune): add SyncService prune integration tests 2026-05-18 21:58:57 +08:00
Research Assistant
5d01c5f1ee feat(prune): integrate prune into sync --prune 2026-05-18 21:57:04 +08:00
Research Assistant
d24f2e822d feat(prune): standalone CLI command
Also fix pre-existing import: has_deep_reading_content moved to obsidian_frontmatter
2026-05-18 21:55:01 +08:00
Research Assistant
f13ba8c3f5 feat(prune): standalone CLI command 2026-05-18 21:54:16 +08:00
Research Assistant
20ff03ed8e fix(prune): protect dir iteration, add OSError handling, improve test coverage 2026-05-18 21:53:14 +08:00
Research Assistant
f10d36d205 feat(prune): core orphan paper cleanup module 2026-05-18 21:48:18 +08:00
Research Assistant
9f013b4cff feat(plugin): render discussion card from .md with MarkdownRenderer 2026-05-18 21:12:06 +08:00
Research Assistant
5ba9ac92c3 feat(discussion): remove JSON output and markdown escaping 2026-05-18 21:09:54 +08:00
Research Assistant
18aa0073c1 Merge branch 'paperforge-stabilization'
# Conflicts:
#	paperforge/memory/vector_db.py
2026-05-18 18:47:07 +08:00
Research Assistant
387a87fef0 fix(test): correct patch target in test_retrieve — must patch embedding.get_embed_status, not status.get_embed_status, because retrieve.py imports from __init__ re-export 2026-05-18 17:38:23 +08:00
Research Assistant
4cc68feb33 chore: remove sentence-transformers from [vector] extra 2026-05-18 17:24:29 +08:00
Research Assistant
98caa83954 test: update vector_db test imports to embedding package 2026-05-18 17:23:37 +08:00
Research Assistant
e8bd3c4131 refactor: update worker/asset_index.py and memory/runtime_health.py imports to embedding package 2026-05-18 17:21:43 +08:00
Research Assistant
37fd996086 refactor(commands): update retrieve.py imports to embedding package 2026-05-18 17:20:50 +08:00
Research Assistant
d4949171e6 refactor(commands): update embed.py imports to embedding package 2026-05-18 17:20:18 +08:00
Research Assistant
56c1871eba refactor(worker): convert vector_db.py to deprecated forwarding shim 2026-05-18 17:19:23 +08:00
Research Assistant
29facca077 refactor(memory): convert vector_db.py to deprecated forwarding shim 2026-05-18 17:18:53 +08:00
Research Assistant
748e440100 feat(embedding): add API-only preflight check 2026-05-18 17:18:04 +08:00
Research Assistant
32d5622ff7 feat(embedding): add get_embed_status() for API-only mode 2026-05-18 17:17:26 +08:00
Research Assistant
755fcf2cd1 feat(embedding): add API-only retrieve_chunks() semantic search 2026-05-18 17:16:51 +08:00
Research Assistant
7e24416712 feat(embedding): add API-only embed_paper() builder 2026-05-18 17:16:15 +08:00
Research Assistant
85b818b0e7 feat(embedding): add build state persistence 2026-05-18 17:15:40 +08:00
Research Assistant
c9cd9ad03e feat(embedding): add ChromaDB collection manager (store only) 2026-05-18 17:14:50 +08:00
Research Assistant
7bb53dd48d feat(embedding): add OpenAI-compatible embedding provider 2026-05-18 17:14:18 +08:00
Research Assistant
66e1afbe6d feat(embedding): add EmbeddingProvider ABC 2026-05-18 17:13:40 +08:00
Research Assistant
5ea4a10b1c feat(embedding): add config reader for API settings 2026-05-18 17:13:16 +08:00
Research Assistant
1a72b06a82 feat(embedding): create embedding package skeleton 2026-05-18 17:12:14 +08:00
Research Assistant
cef93fa588 fix: close review findings for auto-sync, sync PFResult, and global actions
Remove invalid sync --key path from OCR auto-refresh, surface memory rebuild
failures in sync PFResult instead of swallowing them, and complete the
persistent Global action group with Status + Repair.
2026-05-16 23:48:34 +08:00
Research Assistant
f2046e381d feat: progressive disclosure UX (Package D)
Staged setup wizard gating: OCR key and Zotero data no longer block first sync.
Persistent core action visibility: Sync, OCR, Doctor always on Global/Home.
Collapsed Advanced section in Settings for Memory Layer + Vector DB.
OCR/Zotero keys downgraded from blocking validation to optional warnings.
2026-05-16 22:54:05 +08:00
Research Assistant
efc8da0b12 docs: reset documentation IA (readme entry pages, tutorial/troubleshooting split, AGENTS agent-only, pure command ref, maintainer guide)
Separate audiences: README as navigation entry, getting-started as canonical tutorial,
troubleshooting as failure recovery, AGENTS as agent-only operating contract,
COMMANDS as pure reference, maintainer-guide for release/versioning/architecture.
2026-05-16 22:47:00 +08:00
Research Assistant
ed95e0f565 feat: runtime contract hardening + skill/command truth alignment (Package A+B)
Atomic snapshots, canonical index mutation serialization, sync post-clean truth,
plugin path config-awareness, embed stop signal honesty, full snapshot bootstrap,
pf_ prefix unification, workflow command/lifecycle/path corrections,
mechanical/cognitive route separation with unknown-command guard.
2026-05-16 22:38:43 +08:00
Research Assistant
53736ab841 fix: i18n hardcoded English, use cached Python, execFile for pip/cache 2026-05-16 00:57:34 +08:00
Research Assistant
f8631c4545 i18n: update openai key desc — model is user-defined below 2026-05-16 00:41:25 +08:00
Research Assistant
d3ef8062e5 fix: add missing require execFile + instant UI clear on mode toggle 2026-05-16 00:34:09 +08:00
Research Assistant
31ae09fac9 feat: make API mode the default (dropdown order + settings default) 2026-05-16 00:28:10 +08:00
Research Assistant
ae57e081a1 i18n: mode-specific dep install/missing text (API→openai only, local→all three) 2026-05-16 00:19:56 +08:00
Research Assistant
dc25b2fa35 fix: detach embed build process from settings tab (survive close) 2026-05-16 00:12:09 +08:00
Research Assistant
18c3ef9ab0 fix: regenerate vector runtime snapshot on vector mode toggle 2026-05-16 00:05:44 +08:00
Research Assistant
406f41700e fix: mode-aware dep check and install (API→openai only, local→chromadb+sentence-transformers) 2026-05-16 00:03:30 +08:00
Research Assistant
241b8b6d8c fix: inline memory-state into main.js (Obsidian plugins cannot require local files) 2026-05-15 23:54:49 +08:00
Research Assistant
1a9619cb1a fix: move memory-state.js to plugin root for Electron require resolution 2026-05-15 23:52:32 +08:00
Research Assistant
52aa478b69 feat: first-launch snapshot migration (generate runtime-health once if missing) 2026-05-15 23:38:48 +08:00
Research Assistant
f612b191fc feat: async snapshot refresh after heavy operations complete 2026-05-15 23:38:01 +08:00
Research Assistant
871a1574db refactor: replace Python exec with memory-state snapshot reads + _callPython wrapper 2026-05-15 23:35:12 +08:00
Research Assistant
7f865f3df2 fix: add snapshot write to memory status command (not just general status) 2026-05-15 23:14:42 +08:00
Research Assistant
3581bbfba0 feat: Python writes canonical runtime snapshot files for JS reads 2026-05-15 23:06:13 +08:00
Research Assistant
03e38ec1b6 feat: add JS-native file-based memory state reader module 2026-05-15 22:55:40 +08:00
Research Assistant
ece9881d61 docs: v3 — snapshot mandate, degradation policy, first-launch migration, async refresh 2026-05-15 22:31:37 +08:00
Research Assistant
6231c71fdc docs: revise JS-first memory state — Python writes snapshots, JS reads files only 2026-05-15 22:24:26 +08:00
Research Assistant
207d651723 docs: JS-native memory state — spec, plan, and UX audit 2026-05-15 22:11:45 +08:00
Research Assistant
95f30013c3 fix: add build complete notice; remove duplicate display call 2026-05-15 21:35:15 +08:00
Research Assistant
6c00318866 fix: add missing chunker module; restore deleted vector_db.py 2026-05-15 21:27:22 +08:00
Research Assistant
d929b23c66 fix: show error notification on embed build failure; collect stderr 2026-05-15 21:01:08 +08:00
Research Assistant
2abe10bb48 fix: relax vector dep check — openai not required for local mode 2026-05-15 18:16:40 +08:00
Research Assistant
7d58fe88fb fix: move --vault before subcommand in dashboard memory health check 2026-05-15 18:12:05 +08:00
Research Assistant
c2494eb020 fix: reorder table drops to respect FK constraints; add rebuild logging 2026-05-15 17:42:10 +08:00
Research Assistant
3093c6afeb feat: add Rebuild button for memory layer in plugin settings 2026-05-15 17:24:10 +08:00
Research Assistant
97d8c4acda docs: add memory runtime health spec and regression helpers 2026-05-15 01:29:54 +08:00
Research Assistant
ab1538bbc0 chore: fix paperforge skill CLI preflight and vault flag ordering 2026-05-15 01:27:41 +08:00
Research Assistant
6b62dab51f feat: rehydrate vector UI from persistent state; add memory layer to dashboard system status 2026-05-15 01:17:41 +08:00
Research Assistant
03cc2d2efd feat: add runtime-health CLI command 2026-05-15 01:16:16 +08:00
Research Assistant
e57f7b9e4b feat: add layered runtime health computation 2026-05-15 01:15:39 +08:00
Research Assistant
1be3b99464 feat: persist embed lifecycle and add stop command 2026-05-15 01:15:07 +08:00
Research Assistant
6c58493ff6 feat: add persistent vector build state helpers 2026-05-15 01:13:12 +08:00
Research Assistant
f9088c30d4 chore: restore manifest version to match __init__ (1.5.6rc3) 2026-05-15 00:39:12 +08:00
Research Assistant
239e1696d0 feat: embed build background progress with pause/stop 2026-05-15 00:30:50 +08:00
Research Assistant
058132e6ea chore: manifest version back to 1.5.5 (stable) 2026-05-15 00:22:42 +08:00
Research Assistant
afb344d094 bump: 1.5.6rc2 -> 1.5.6rc3 2026-05-15 00:16:16 +08:00
Research Assistant
ecf8e3525b fix: add --resume CLI arg and get_collection import for embed build 2026-05-15 00:16:06 +08:00
Research Assistant
822a9d69ac feat: add --resume flag for incremental vector embed build 2026-05-15 00:15:25 +08:00
Research Assistant
583e294090 fix: guard features object in settings to prevent crash on first render 2026-05-14 23:48:54 +08:00
Research Assistant
2b679d61ff bump: 1.5.6rc1 -> 1.5.6rc2 2026-05-14 23:34:56 +08:00
Research Assistant
dd2f814375 fix: auto-build memory DB after sync so search works immediately 2026-05-14 23:34:23 +08:00
Lin Zhaoxuan
1eadacee0e
Merge pull request #8 from LLLin000/feature/memory
Research Memory Runtime + User-Side Stabilization
2026-05-14 23:06:55 +08:00
Research Assistant
f054193407 fix: update package-data from literature-qa to skills/paperforge/** 2026-05-14 22:58:03 +08:00
Research Assistant
6643229f93 fix: refresh_paper FTS delete-before-upsert, import error checking 2026-05-14 22:47:48 +08:00
Research Assistant
a76cb21f09 fix: import_reading_log to JSONL, correction JSONL-first, events.py wrapper 2026-05-14 22:37:55 +08:00
Research Assistant
888bbbba02 fix: pf_bootstrap verified tuple return, engineering review dimensions 2026-05-14 22:36:12 +08:00
Research Assistant
ce86effe40 fix: dedupe correction import on rebuild, clean FTS row on refresh 2026-05-14 22:35:35 +08:00
Research Assistant
62cbb6110b feat: retrieve empty index guard, embed status check, HF download hint 2026-05-14 21:59:25 +08:00
Research Assistant
2c71643e41 fix: remove ghost settings code, add vector deps, add embed preflight 2026-05-14 21:56:28 +08:00
Research Assistant
002173f768 feat: safe FTS search with token-quote and LIKE fallback 2026-05-14 21:50:29 +08:00
Research Assistant
054ca3e1b4 feat: permanent correction-log.jsonl, fix original_id field alignment 2026-05-14 21:48:21 +08:00
Research Assistant
9b0bc59589 fix: bootstrap vault_config nest, python fallback with verified flag 2026-05-14 21:47:43 +08:00
Research Assistant
f248f81d87 refactor: unify reading-log reads to JSONL, deprecate paper_events writes 2026-05-14 21:44:05 +08:00
Research Assistant
5f07a8f729 fix: reset nopdf OCR status to pending when paper re-enters queue 2026-05-14 18:43:48 +08:00
Research Assistant
df135bff68 refactor: unify skills into paperforge compound skill (6 workflows) 2026-05-14 17:56:25 +08:00
Research Assistant
95bfb227b5 feat: add METHODOLOGY_COMPACT.md for agent guidance 2026-05-14 17:51:18 +08:00
Research Assistant
5a44926cc0 feat: import JSONL into DB on memory build 2026-05-14 17:48:23 +08:00
Research Assistant
06a3f2bf97 feat: add project-log CLI command with JSONL write + auto-render 2026-05-14 17:47:43 +08:00
Research Assistant
b1aa22290e feat: add paper-context CLI command for reading-log safety loop 2026-05-14 17:44:20 +08:00
Research Assistant
d16b6c7d59 feat: upgrade reading-log to JSONL with context/tags/project fields and auto-render 2026-05-14 17:31:32 +08:00
Research Assistant
2631edb81c fix: align JSONL field names with spec (type/title, add verified) 2026-05-14 17:20:29 +08:00
Research Assistant
0d1ca3a2be feat: add permanent JSONL storage layer for reading-log and project-log 2026-05-14 17:08:10 +08:00
Research Assistant
5493e28d66 feat: add reading_log and project_log tables to memory schema 2026-05-14 16:51:14 +08:00
Research Assistant
cfc075555b fix(plugin): fall back to global mode when Base domain has no matching papers 2026-05-14 01:49:38 +08:00
Research Assistant
97d9715ea5 fix(plugin): open .base file directly instead of file-explorer + trim domain basename 2026-05-14 01:41:51 +08:00
Research Assistant
d6960a78a8 fix(plugin): use getLeavesOfType + revealLeaf to focus existing file-explorer 2026-05-14 01:39:26 +08:00
Research Assistant
9af8bbfb28 fix(plugin): simplify file-explorer open to enable() call 2026-05-14 01:38:06 +08:00
Research Assistant
b4632e3205 fix(plugin): replace deprecated revealLeaf().setViewState with internalPlugins toggle 2026-05-14 01:35:22 +08:00
Research Assistant
6f6c1ae19d spec: remove copy icon — clean click-to-copy with dashed underline only 2026-05-14 01:31:43 +08:00
Research Assistant
eed48178fe spec: dashboard copy interaction + per-paper metadata enhancement 2026-05-14 01:21:52 +08:00
Research Assistant
caf7c10041 i18n(plugin): translate all remaining Features tab strings to en/zh 2026-05-14 01:07:50 +08:00
Research Assistant
455c83d05e fix(plugin): restore API settings + hide HF in API mode 2026-05-14 00:58:30 +08:00
Research Assistant
9c3a4d6e21 i18n(plugin): translate local model descriptions to en/zh 2026-05-14 00:55:16 +08:00
Research Assistant
6c86acf271 fix(plugin): undeclared customText variable in _renderHfMirror 2026-05-14 00:53:20 +08:00
Research Assistant
c0059e6203 i18n(plugin): translate all Feature tab UI strings to en/zh 2026-05-14 00:51:49 +08:00
Research Assistant
40ed946bb7 feat(plugin): i18n descriptions for Skills/Memory/Vector + collapsible vector config 2026-05-14 00:40:33 +08:00
Research Assistant
a52b1c78d2 fix: get_embed_status reads API model; defer display() after async status refresh 2026-05-14 00:18:03 +08:00
Research Assistant
d89a6275a6 fix: _getCurrentModelKey reads actual API model instead of hardcoded value 2026-05-13 22:32:46 +08:00
Research Assistant
cd4fea2217 debug: log API base_url to check env var passthrough 2026-05-13 22:25:20 +08:00
Research Assistant
1d308e3b72 fix: pass API key/base/model as env vars to avoid saveSettings race 2026-05-13 22:22:37 +08:00
Research Assistant
a3f98865dc feat(plugin): click terminal output to copy to clipboard 2026-05-13 22:13:00 +08:00
Research Assistant
af3fbc95a7 fix: add openai to deps check + install cmd for API mode 2026-05-13 22:06:42 +08:00
Research Assistant
5ae4f726fa fix: add _renderApiConfig method, remove broken import() syntax 2026-05-13 22:01:21 +08:00
Research Assistant
9dc5ef3fff feat: API model as text field (custom any name) + fix Python duplicate 2026-05-13 21:55:09 +08:00
Research Assistant
f718574087 feat: urllib-based model download bypasses HF hub + HF_TOKEN field 2026-05-13 21:33:09 +08:00
Research Assistant
beda4119e8 feat: huggingface_hub.set_endpoint() mirror + API base_url support 2026-05-13 21:03:24 +08:00
Research Assistant
8bf9476a76 fix: store Text component ref instead of Setting for setValue 2026-05-13 20:54:07 +08:00
Research Assistant
49649439e2 fix: extract _renderHfMirror method, remove orphaned module-level code 2026-05-13 20:24:04 +08:00
Research Assistant
b172ed1974 feat(plugin): user skills collapsed by default 2026-05-13 19:22:08 +08:00
Research Assistant
3fefccb841 fix: Python no longer overrides HF_ENDPOINT from stale settings 2026-05-13 19:21:21 +08:00
Research Assistant
b011b44d7a feat(plugin): HF mirror dropdown with presets + custom endpoint 2026-05-13 19:19:39 +08:00
Research Assistant
48be9b676f fix(plugin): check model cache integrity not just directory existence 2026-05-13 19:17:12 +08:00
Research Assistant
2a78086f79 feat: HF mirror endpoint support for model downloads behind firewalls 2026-05-13 19:15:43 +08:00
Research Assistant
a70480718c fix: lighter terminal output box + cache embedding model across papers 2026-05-13 19:12:52 +08:00
Research Assistant
1d3b8723e2 fix(plugin): improve skills spacing - group wrappers with even padding 2026-05-13 19:03:11 +08:00
Research Assistant
3c5505316b fix(plugin): preserve skills collapse state across tab/model re-renders 2026-05-13 19:00:54 +08:00
Research Assistant
886049dde3 feat: vector auto-embed on OCR complete + Uninstall button cache detection 2026-05-13 18:58:00 +08:00
Research Assistant
df456fb0ec feat(plugin): live terminal output + model descriptions + uninstall model button 2026-05-13 18:52:26 +08:00
Research Assistant
7b31d21a07 feat(plugin): rewrite Vector DB section with state machine 2026-05-13 18:40:01 +08:00
Research Assistant
6983afd484 fix(plugin): use CSS rotate for arrow instead of different unicode chars 2026-05-13 18:20:18 +08:00
Research Assistant
3b80770568 fix(plugin): always-on scrollbar + stable collapse header positions 2026-05-13 18:18:49 +08:00
Research Assistant
108e2f7d9b fix(plugin): create header before content in skills collapsible 2026-05-13 18:14:31 +08:00
Research Assistant
bd34f7da38 fix(plugin): skill collapse arrow direction + render into content div 2026-05-13 18:11:57 +08:00
Research Assistant
076774dac6 feat(plugin): add collapsible toggle for System/User skill groups 2026-05-13 18:05:52 +08:00
Research Assistant
6cb00c5c74 feat(plugin): add sync timestamp + spinner + manual sync button 2026-05-13 17:52:05 +08:00
Research Assistant
314dda53e5 fix(plugin): clean up debug logs, deps check working with resolvePythonExecutable + async exec 2026-05-13 17:39:10 +08:00
Research Assistant
8580f16598 fix(plugin): replace async deps check with sync execSync, remove dead _resolvePythonAsync 2026-05-13 17:34:40 +08:00
Research Assistant
b8d3daf66f perf: executemany batching in builder + file read consolidation 2026-05-13 17:17:08 +08:00
Research Assistant
7df1f38f6d perf: merge dashboard queries into single GROUP BY 2026-05-13 17:08:11 +08:00
Research Assistant
2dd6b0d86b refactor: extract build_paper_row to shared _columns module 2026-05-13 17:07:14 +08:00
Research Assistant
8babd361f2 perf: single frontmatter parse in _build_entry 2026-05-13 17:03:55 +08:00
Research Assistant
748f32b282 perf: autoSync runs sync not full build, 30s→120s poll, remove unused harness file 2026-05-13 17:02:31 +08:00
Research Assistant
5ff3140a80 perf: fix FTS double-insert, drop trigger before bulk insert 2026-05-13 17:01:28 +08:00
Research Assistant
e91dfd8c45 perf: refresh_paper accepts entry dict, skip full index read 2026-05-13 16:58:39 +08:00
Research Assistant
d2c0c891ad docs(spec): 10-point memory layer performance optimization 2026-05-13 16:52:10 +08:00
Research Assistant
332558a72a feat(plugin): auto-poll exports/ocr for seamless memory layer updates 2026-05-13 16:35:07 +08:00
Research Assistant
7b3326db61 fix(skill): add language rule — field labels in English, content in user's language 2026-05-13 16:24:09 +08:00
Research Assistant
d8c9cc3cef fix(cli): support multiline fields + bilingual labels in reading-log parser 2026-05-13 16:23:01 +08:00
Research Assistant
f747c18df0 feat(cli): migrate dashboard to SQLite with file scan fallback 2026-05-13 16:13:38 +08:00
Research Assistant
12cb670016 feat(cli): add reading-log --validate/--import/--lookup commands 2026-05-13 16:12:23 +08:00
Research Assistant
93ded8e29b feat(skill): add methodology extraction skill (pure prompt) 2026-05-13 16:04:46 +08:00
Research Assistant
73a9ad3868 fix(skill): add strict reading-log template to logging SKILL.md 2026-05-13 16:03:27 +08:00
Research Assistant
6cbcce84e7 docs(spec): log format validation, reading-log import/lookup, methodology skill, dashboard SQLite 2026-05-13 16:02:50 +08:00
Research Assistant
ceb4d8c89f fix(plugin): remove Easy Memory Layer toggle, always-on status display 2026-05-13 16:01:14 +08:00
Research Assistant
216bc65d9d fix(skill): remove ambiguous trigger '这段有什么值得记的' from logging skill 2026-05-13 01:07:58 +08:00
Research Assistant
c3f79e69bb fix(skill): route '这段有什么值得记的' to reading branch 2026-05-13 01:07:08 +08:00
Research Assistant
2c79bf64e3 fix(skill): add routing table (reading vs working), clean up stale sections 2026-05-13 01:05:38 +08:00
Research Assistant
06b8db07a4 feat(skill): rename logging skill, natural language triggers, no /pf- prefix 2026-05-13 01:04:02 +08:00
Research Assistant
2b52499304 fix(plugin): wrap System/User Skills in dark gray box, add folder icon button to Agent Platform 2026-05-13 00:58:22 +08:00
Research Assistant
a9cf2352fd fix(skill): add source: paperforge to both skill frontmatter for system detection 2026-05-13 00:53:41 +08:00
Research Assistant
2f77ad4bcb feat(harness): expand skill description triggers, add priority rules against manual grep 2026-05-13 00:50:17 +08:00
Research Assistant
b1b1d50129 feat(harness): add pf_search.py unified search entry + update bootstrap with memory_layer field 2026-05-13 00:46:37 +08:00
Research Assistant
670d3eb5f3 fix(plugin): rename toggle to Easy Memory Layer with clarifying description 2026-05-12 23:54:36 +08:00
Research Assistant
fb3badab4f fix(plugin): reorder features tab — Skills first, then Memory Layer containing Vector DB 2026-05-12 23:54:06 +08:00
Research Assistant
eb88b829a7 fix(plugin): cache memory/vector status, add manual refresh, skip re-check on tab switch 2026-05-12 23:45:24 +08:00
Research Assistant
9b3e844eb8 chore: add pre-commit JS syntax hook + stage missing vector CLI files 2026-05-12 23:34:24 +08:00
Research Assistant
f9ac0cb243 fix(plugin): repair brace mismatches from refactoring 2026-05-12 23:32:03 +08:00
Research Assistant
d90be02a82 fix(plugin): fix try/catch mismatches in vector deps + embed status blocks 2026-05-12 23:16:17 +08:00
Research Assistant
10d9ef5100 fix(plugin): use resolvePythonExecutable() everywhere instead of settings.python_path 2026-05-12 23:14:29 +08:00
Research Assistant
2cae6c1b54 fix(plugin): guard python_path before pip install, show hint when Python not configured 2026-05-12 23:11:21 +08:00
Research Assistant
a3c32a03cc fix(plugin): async pip install with persistent notice + UTF-8 encoding fix 2026-05-12 23:07:03 +08:00
Research Assistant
cc4fd00f8f fix(plugin): don't render empty memory status div when Python not configured 2026-05-12 23:04:10 +08:00
Research Assistant
442d22a165 fix(plugin): use setText() instead of createEl text option for status/warning divs 2026-05-12 22:59:14 +08:00
Research Assistant
099fbed90a fix(plugin): remove extra closing brace causing SyntaxError 2026-05-12 22:52:49 +08:00
Research Assistant
053b303c2a fix(plugin): remove dead cascading keys, fix skill toggle content sync, remove unused disableMatch 2026-05-12 22:44:37 +08:00
Research Assistant
3532b34710 fix(plugin): single memory toggle + platform skill selector + vector UX improvements 2026-05-12 22:41:49 +08:00
Research Assistant
0d83278f1b feat(plugin): tabbed settings UI (Installation + Features) with skill manager and feature toggles 2026-05-12 22:28:00 +08:00
Research Assistant
9016a8734e docs(spec): add Phase 7 vector retrieval — ChromaDB + local/API embedding + chunking 2026-05-12 21:43:34 +08:00
Research Assistant
2551eec014 fix(spec): add DEFAULT_SETTINGS whitelist note, source: paperforge requirement, CLI toggle read 2026-05-12 21:19:21 +08:00
Research Assistant
fffc0c3d9f docs(spec): plugin settings redesign — tabbed UI, skill manager, feature toggles, vector DB panel 2026-05-12 21:11:15 +08:00
Research Assistant
11be2b8df2 feat(skills): add literature-logging skill (reading-log + working-log) 2026-05-12 20:58:49 +08:00
Research Assistant
babfe06bc3 feat(skills): add /pf-log-reading and /pf-log-session slash commands 2026-05-12 20:55:32 +08:00
Research Assistant
99ab29bc75 feat(memory): add paper_events table + reading-log write/export command 2026-05-12 20:53:33 +08:00
Research Assistant
4ffcd4c1c0 docs(spec): add Phase 6 — paper_events, reading/working logs, vector retrieval 2026-05-12 20:48:09 +08:00
Research Assistant
d4df673088 feat(memory): dashboard reads from SQLite + incremental refresh_paper() 2026-05-12 20:08:46 +08:00
Research Assistant
3ee0320fb9 test(memory): verify agent-context on test vault — 150 papers, 26 collections, 4 rules 2026-05-12 20:00:16 +08:00
Research Assistant
551abd0e15 feat(cli): add agent-context command for agent bootstrap 2026-05-12 19:59:12 +08:00
Research Assistant
2b91e09996 feat(memory): add agent context query module 2026-05-12 19:55:58 +08:00
Research Assistant
5f7f2cd317 docs(plan): add agent-context implementation plan 2026-05-12 19:54:19 +08:00
Research Assistant
eedf02c462 docs(spec): add Memory Layer Phase 2-5 design (agent-context, dashboard, refresh, retrieve) 2026-05-12 19:44:38 +08:00
Research Assistant
4bb750b2db fix(memory): match FTS column names to papers table (authors_json, collections_json) 2026-05-12 19:01:41 +08:00
Research Assistant
1acbeaae23 feat(memory): add FTS5 full-text search with paperforge search command 2026-05-12 18:58:25 +08:00
Research Assistant
5673f682a2 fix(memory): restore row.keys() iteration (sqlite3.Row iterates values, not keys) 2026-05-12 18:33:33 +08:00
Research Assistant
6c6b8ce7a1 feat(frontmatter): add citation_key field and alias from BBT citationKey 2026-05-12 18:28:53 +08:00
Research Assistant
02c1e5b8a0 bump: 1.5.5 -> 1.5.6rc1 (Memory Layer RC1) 2026-05-12 18:11:37 +08:00
Research Assistant
339ffe2b56 feat(memory): add schema exports to __init__.py 2026-05-12 18:01:21 +08:00
Research Assistant
95ca8fceb8 style(memory): apply ruff fixes (ternary, nested-if, dict-keys) 2026-05-12 18:00:52 +08:00
Research Assistant
65cbf867e6 test(memory): add integration test for memory build/status workflow 2026-05-12 17:59:37 +08:00
Research Assistant
3c906e8942 feat(cli): add memory build/status and paper-status commands 2026-05-12 17:52:30 +08:00
Research Assistant
afcbd3ce27 feat(memory): add query module for paper lookup and status check 2026-05-12 17:47:30 +08:00
Research Assistant
f6bc234aa7 feat(memory): add builder module that populates SQLite from formal-library.json 2026-05-12 17:44:03 +08:00
Research Assistant
fb17c58020 feat(memory): add schema module with table definitions and tests 2026-05-12 17:40:10 +08:00
Research Assistant
772954fca4 feat(memory): add db.py with connection and path resolution 2026-05-12 17:35:19 +08:00
Research Assistant
139d5b673e feat(config): add memory_db path key for Memory Layer 2026-05-12 17:32:59 +08:00
Research Assistant
da4ef951ac fix(setup): overwrite skills on wizard re-run, never overwrite AGENTS.md 2026-05-12 02:13:03 +08:00
Research Assistant
2bb0c428d7 feat(frontmatter): collection_path as YAML list, add collection_tags; runtime skill deploy; OCR progress notices 2026-05-12 02:03:31 +08:00
Research Assistant
696cd6f15f fix(ocr): return real exit code, add real-time progress output to stdout, show Obsidian Notices 2026-05-12 00:55:30 +08:00
Research Assistant
287c413d5d bump: 1.5.4 -> 1.5.5 2026-05-12 00:55:12 +08:00
Research Assistant
6f4d11b05c fix(literature-qa): fix stale references, define \, use glob for key lookup, remove /pf-end slash 2026-05-12 00:16:43 +08:00
Research Assistant
26b66d190e fix(literature-qa): prefer glob over resolve-key for quick key lookup, remove rg dependency 2026-05-12 00:11:24 +08:00
Research Assistant
316b8bdcb2 feat: restructure literature-qa v2 — SKILL.md as central hub with decision tree, add multi-reading, simplify refs 2026-05-11 23:58:46 +08:00
Research Assistant
dd8f7307d3 fix(literature-qa): simplify vault-knowledge — all path discovery via pf_bootstrap, remove manual paths step 2026-05-11 23:37:13 +08:00
Research Assistant
8010708102 fix(literature-qa): unify all references to use pf_bootstrap, , ; prohibit path guessing 2026-05-11 23:34:27 +08:00
Research Assistant
9707fb7f1b fix(literature-qa): add Python discovery sequence, require not system python 2026-05-11 23:25:10 +08:00
Research Assistant
d570aa409b fix(literature-qa): prohibit hardcoded path construction in skill references 2026-05-11 23:17:05 +08:00
Research Assistant
aec69f0179 docs: clarify agent triggers as phrases not plugins, add natural language triggers, fix README wizard flow 2026-05-11 22:41:19 +08:00
Research Assistant
bab889dc77 fix(literature-qa): add mandatory pre-flight, vault discovery, STAGE state machine to prevent agent drift 2026-05-11 22:27:45 +08:00
Research Assistant
a524290879 fix: add v prefix to bump.py tags to match workflow trigger 2026-05-11 21:40:01 +08:00
Research Assistant
f9dc28b44b bump: 1.5.3 -> 1.5.4 2026-05-11 21:34:36 +08:00
Research Assistant
49ee42f3f6 fix: use item['title'] instead of undefined entry in self-healing migration 2026-05-11 21:22:11 +08:00
Research Assistant
a9117a0f8b fix: update ocr auto_analyze and ld_deep search for {key}.md filenames with fallback 2026-05-11 21:13:27 +08:00
Research Assistant
5aecdf93dd feat: change sync to {key}.md, add aliases frontmatter, self-healing rename in migrate 2026-05-11 21:12:29 +08:00
Research Assistant
0c91bded54 feat: change formal note filename to {key}.md, add self-healing migration + alias injection 2026-05-11 21:11:12 +08:00
Research Assistant
ed0da99207 test: update fixtures to {key}.md filename format (red phase) 2026-05-11 21:09:36 +08:00
Research Assistant
fd82c28991 docs: replace git+https install URLs with pip install paperforge (PyPI) 2026-05-11 19:25:38 +08:00
Research Assistant
e42c38e212 fix: bump.py — add UTF-8 encoding to git show, remove release logic (handled by Actions) 2026-05-11 19:25:09 +08:00
Research Assistant
03ea934120 bump: 1.5.2 -> 1.5.3 2026-05-11 19:20:47 +08:00
Research Assistant
6d0a3e6848 style: ruff auto-fix setup_wizard.py (unused imports, f-strings, dead code) 2026-05-11 19:19:40 +08:00
Research Assistant
c28de1bce5 fix: force UTF-8 encoding for all subprocess and stdout on Windows, fix pre-existing logger bug 2026-05-11 19:16:18 +08:00
Research Assistant
f031fd26ef fix(skill): split vault-browse from paper-search, add browsing flow to vault-knowledge 2026-05-11 19:03:38 +08:00
Research Assistant
80aa37a091 feat(skill): add library browsing trigger phrases to paper-search route 2026-05-11 18:54:53 +08:00
Research Assistant
1b0be909fc feat(skill): add vault-knowledge + paper-search reference files, update routing table 2026-05-11 18:49:33 +08:00
Research Assistant
9f82d527cf fix(plugin): show setup-needed hint when paperforge not configured 2026-05-11 18:30:50 +08:00
Research Assistant
5ae92f4eee fix(plugin): skip auto-update when setup not completed 2026-05-11 18:29:33 +08:00
Research Assistant
f537c88a31 fix(plugin): guard _fetchStats against missing _metricsEl 2026-05-11 18:25:05 +08:00
Research Assistant
54ea998032 ci: add contents:write permission for release management 2026-05-11 18:21:16 +08:00
Research Assistant
35bd1f4885 ci: handle existing release in publish workflow 2026-05-11 18:19:32 +08:00
Research Assistant
cb6961bf67 ci: add skip-existing and auto GitHub release creation 2026-05-11 18:17:33 +08:00
Research Assistant
2fb9c7e66d chore: bump version to v1.5.2 2026-05-11 18:15:02 +08:00
Research Assistant
d9aa303cf7 feat(plugin): add console logs showing PyPI vs git install source 2026-05-11 18:10:56 +08:00
Research Assistant
1c010c1c62 ci: explicit PYPI_TOKEN secret in publish workflow 2026-05-11 18:07:08 +08:00
Research Assistant
7bb32f2571 feat: PyPI publish support — install paperforge from PyPI with git fallback 2026-05-11 18:04:17 +08:00
Research Assistant
46e6b85fe5 feat(plugin): enhanced diagnostic — git/PATH/vault path on install failure 2026-05-11 17:51:14 +08:00
Research Assistant
4aeb7e18e6 fix(base): use !zotero_key.isEmpty() filter syntax 2026-05-11 17:47:05 +08:00
Research Assistant
e2b03e8502 docs: update v1.5.1 changelog with all hotfixes 2026-05-11 17:44:56 +08:00
Research Assistant
ac8de5d1b5 fix: prepend v to git tag ref in all pip install URLs 2026-05-11 17:41:59 +08:00
Research Assistant
d8912cff4e debug: log pip stderr on Sync Runtime failure 2026-05-11 17:38:38 +08:00
Research Assistant
b5b25752a8 fix(plugin): pass enriched env through runSubprocess for Sync Runtime button 2026-05-11 17:32:19 +08:00
Research Assistant
1514ad6f53 feat(plugin): cross-platform git detection (win/mac/linux) for pip install PATH 2026-05-11 17:28:34 +08:00
Research Assistant
9a37b4f516 feat(plugin): resolve git via ComSpec and inject into PATH for pip install spawns 2026-05-11 17:26:35 +08:00
Research Assistant
acd1d21334 fix(base): filter by zotero_key != "" instead of filename exclusion 2026-05-11 17:11:51 +08:00
Research Assistant
4b13d8e8d1 fix(base): exclude fulltext.md from Base views to prevent workspace clutter 2026-05-11 17:10:34 +08:00
Research Assistant
5f8396c483 feat(update): add zip fallback when pip/git update fails (e.g. missing git) 2026-05-11 17:04:30 +08:00
Research Assistant
a6b90f8538 chore: remove CI workflows pending rewrite 2026-05-11 17:00:23 +08:00
Research Assistant
755359dc59 chore: bump version to v1.5.1 2026-05-11 16:50:07 +08:00
Research Assistant
560c6b5121 hotfix: fix Base filter syntax error, = to == 2026-05-11 16:43:58 +08:00
Research Assistant
2220fe0fe5 hotfix: remove py launcher from auto-detection to prevent spawn ENOENT on Windows 2026-05-11 16:40:22 +08:00
Research Assistant
112b001466 docs: update README version refs to v1.5.0, add Dashboard three-mode / pf-end sections 2026-05-11 12:55:31 +08:00
Research Assistant
20c7f475f2 docs: add v1.5.0 changelog entries 2026-05-11 00:56:39 +08:00
Research Assistant
08c74fd8da fix: deep_reading_status read from frontmatter, key extraction walkup, remove body status fields
- _build_entry: read deep_reading_status from frontmatter first, body detection fallback

- _extractZoteroKeyFromPath: walk up directory tree for 8-char key (handles ai/discussion.md etc.)

- frontmatter_note: remove duplicate PDF/OCR/deep_reading status from body (frontmatter is source of truth)
2026-05-11 00:52:07 +08:00
Research Assistant
b63915953e ci: add contents:write permission to release workflow 2026-05-11 00:23:48 +08:00
Research Assistant
bc150d3bf6 chore: bump version to v1.5.0 2026-05-11 00:21:35 +08:00
Research Assistant
7933ad8c68 test: update headless_setup tests for refactored literature-qa skill directory
Refactored deploy_skills service creates a single literature-qa skill dir

instead of individual pf-deep/pf-paper/etc. Update all 4 agent

platform tests to check for literature-qa instead of old names.
2026-05-11 00:18:24 +08:00
Research Assistant
d768f5bcb0 fix(dashboard): use same wikilink parser as Open PDF button for PDF detection 2026-05-11 00:17:21 +08:00
Research Assistant
a11e62c6aa feat(dashboard): PDF files now trigger per-paper mode via index pdf_path match 2026-05-11 00:15:42 +08:00
Research Assistant
2f0f417b7c fix(setup,test): replace orphaned imported_skills variable and update bootstrap test
headless_setup Phase 7 used imported_skills which was removed during

skill_deploy refactor. Use skill_result['skill_deployed'] instead.

Also update bootstrap test that asserted old command_files string.
2026-05-11 00:11:00 +08:00
Research Assistant
dceb1f9661 Merge branch 'fix/setup-v2' 2026-05-11 00:06:20 +08:00
Research Assistant
232dd1f453 test: update AGENT_CONFIGS tests for refactored AGENT_SKILL_DIRS flat dict
Setup wizard no longer defines AGENT_CONFIGS; the refactored

skill_deploy.py exports AGENT_SKILL_DIRS instead. Update

test imports and assertions accordingly.
2026-05-11 00:05:59 +08:00
Research Assistant
ec778c3668 fix(setup): align setup_wizard and skill_deploy API with refactored master
Use AGENT_SKILL_DIRS (flat dict) instead of AGENT_CONFIGS (nested),

matching the skill_deploy.py refactor already on master.
2026-05-11 00:03:03 +08:00
Research Assistant
a73b1681e7 fix(setup): use AGENT_CONFIGS import to match master skill_deploy.py API
fix/setup branched from master where skill_deploy still exports

AGENT_CONFIGS (not AGENT_SKILL_DIRS which was renamed later).
2026-05-10 23:54:33 +08:00
Research Assistant
be3b01e7bf fix(dashboard): workspace path detection now triggers paper mode for any file in workspace dir
- Remove _findEntry() precondition — works even if index not yet loaded
- Add case-insensitive flag to key regex (/i)
2026-05-10 23:40:35 +08:00
Lin Zhaoxuan
d4c37f77a0
Merge pull request #7 from LLLin000/feature/skill-refine
feat: unified release — skill redesign + deep-finalize + sync safety + dashboard v2
2026-05-10 23:32:23 +08:00
Lin Zhaoxuan
7abf91c63a
Merge pull request #6 from LLLin000/fix/setup
fix(setup,plugin): rewrite BBT detection for Zotero 7 .xpi compatibility
2026-05-10 23:31:44 +08:00
Research Assistant
5138a70645 merge: integrate dashboard-refine (deep-finalize + slug-freeze) into skill-refine
Resolved conflicts:
- styles.css: take dashboard-refine (more refined CSS)
- SKILL.md, deep-reading.md, paper-resolution.md: take skill-refine (modular skill redesign)
2026-05-10 23:28:13 +08:00
Research Assistant
c44c16bf80 refactor(skills): simplify skill deployment — single copytree for all platforms
- Remove format dispatch (flat_command/skill_directory/rules_file) — all platforms unified
- skill_deploy.py: 257→81 lines, only AGENT_SKILL_DIRS + copytree + AGENTS.md
- AgentInstaller switches to vault-local paths, removes deploy_commands step
- Remove _deploy_skills dead code in update.py
2026-05-10 23:22:42 +08:00
Research Assistant
5bcfc8d1cb fix(setup,plugin): rewrite BBT detection for Zotero 7 .xpi compatibility
Setup wizard (Python):

- Replace broken manual_path direct-candidate scan with unified platform-path-first approach

- Use _looks_like_bbt() — normalize to alnum+lower, match 'betterbibtex'

- Accept both .xpi files (Zotero 7) and directories (Zotero 6)

- Correct Linux profile path (.zotero/zotero/<random>, not .zotero/zotero/Profiles)

Plugin (JS):

- Remove isDirectory() restriction in scanBbtUnderProfiles/scanBbtDirectChildren

- Accept .xpi file entries for Zotero 7 compatibility

- Also remove all control_dir references (CLI argument removed in v1.4.17)
2026-05-10 23:18:14 +08:00
Research Assistant
ede222edc9 fix(plugin): remove all control_dir references — CLI argument was removed in v1.4.17
- Remove --control-dir from setup args (CLI no longer accepts it)

- Remove control_dir from DEFAULTS, config parser, valid path keys

- Remove control_dir from settings assignment and JSDoc

- Remove dir_index display and validate_index check
2026-05-10 23:05:22 +08:00
Research Assistant
c17972a17a fix(sync): freeze workspace slug + frontmatter-only update to prevent deep-reading data loss
- Slug freeze: reuse existing workspace dir when title slug changes in Zotero
- Frontmatter-only: for existing notes, replace only YAML block, never touch body
- extract_preserved_deep_reading: match both ##精读 and ##🔍精读 + skip placeholder-only sections
2026-05-10 22:31:16 +08:00
Research Assistant
9dc7ff4322 style: align collection workflow overview with global library snapshot
- Match outer frame padding/background/shadow to library-snapshot

- Match inner stage card padding/background/layout to snapshot-pill

- Use align-items: stretch on funnel (pill parity), arrow stays centered

- Reduce collection-header bottom gap for tighter domain-to-card spacing

- Synchronize stage-label font-size (12px -> 11px)
2026-05-10 22:22:31 +08:00
Research Assistant
914e47636e docs: update version reference to v1.4.18, note setup wizard fix in changelog 2026-05-10 21:53:02 +08:00
Research Assistant
bf990d79a0 feat: add deep-finalize command — signal dashboard on /pf-deep completion
- new command paperforge deep-finalize <key>: sets deep_reading_status=done in frontmatter + refreshes index
- dashboard now only auto-refreshes on formal-library.json changes (removed per-note modify handler)
- pf-deep reference updated with Post-Processing section instructing agent to call deep-finalize at end
2026-05-10 21:50:27 +08:00
Research Assistant
d91afde635 Revert "docs: update version reference to v1.4.18 and document setup wizard fix"
This reverts commit d94c2501af.
2026-05-10 21:38:10 +08:00
Research Assistant
d94c2501af docs: update version reference to v1.4.18 and document setup wizard fix 2026-05-10 21:36:10 +08:00
Research Assistant
8bfdfc2360 test: update bootstrap test to match fixed agents_src code 2026-05-10 21:05:16 +08:00
Research Assistant
cfe00a9a64 test: update bootstrap test to match fixed agents_src code 2026-05-10 21:05:05 +08:00
Research Assistant
5f17db93fe fix(setup): resolve NameError for undefined agents_src in Phase 7 verification 2026-05-10 20:59:57 +08:00
Research Assistant
8b8c0788e3 fix(skills): narrow description triggers to avoid false matches 2026-05-10 20:56:28 +08:00
Research Assistant
59a024abba refactor(skills): modular literature-qa skill with router-first architecture
- Replace 6 scattered pf-*.md files with single SKILL.md router + 4 reference files
- Add paper_resolver.py: deterministic key/DOI/field search (4 subcommands)
- Remove pf-sync/ocr/status (CLI-only commands, no skill wrapper needed)
- Move chart-reading/ into references/ for flat structure
- Make ld_deep.py --vault optional (auto-detect from cwd)
- Add 26 unit tests for paper_resolver
- All paths dynamically resolved from paperforge.json, zero hardcoding
2026-05-10 20:56:28 +08:00
Research Assistant
1a447e989e feat: dashboard ui refine — arrow icons, maillard colors, responsive grid, setup bugfix
Dashboard UI:

- Replace text expand/collapse with SVG arrow + clickable gradient container

- Map agent_platform key to display name (OpenCode, not opencode)

- Maillard/Morandi palette for OCR progress bars (pending brown, done deep green)

- Shorten 'Needs Attention' to 'Attention' to prevent label wrap

- Responsive workflow overview: CSS Grid + container queries (narrow: 2x2, wide: 4x1 with max-width 160px stop)

Setup Wizard:

- Fix Phase 7 verification crash (undefined agents_src/agents_dst variables)

Skill restructure:

- Move chart-reading references under references/ directory

- Remove old pf-*.md script files (deployed via skill_deploy service)

- Add new reference files (deep-reading, paper-qa, paper-resolution, save-session)
2026-05-10 20:56:27 +08:00
Research Assistant
47038e6864 style: tighten collection header spacing, fix u00B7 encoding, add stage max-width
- Fix CSS unicode escape: \\u00B7 -> literal middle dot character

- Remove 'papers' count line in collection header

- Tighten collection-header padding from 64px to 14px top only

- Reset collection-title margin to 0

- Add max-width: 160px + justify-self: center to workflow stages

- workflow-stage-label font-size: 11px -> 12px
2026-05-10 20:52:22 +08:00
Research Assistant
365498bded feat: dashboard ui refine — arrow icons, maillard colors, responsive grid, setup bugfix
Dashboard UI:

- Replace text expand/collapse with SVG arrow + clickable gradient container

- Map agent_platform key to display name (OpenCode, not opencode)

- Maillard/Morandi palette for OCR progress bars (pending brown, done deep green)

- Shorten 'Needs Attention' to 'Attention' to prevent label wrap

- Responsive workflow overview: CSS Grid + container queries (narrow: 2x2, wide: 4x1 with max-width 160px stop)

Setup Wizard:

- Fix Phase 7 verification crash (undefined agents_src/agents_dst variables)

Skill restructure:

- Move chart-reading references under references/ directory

- Remove old pf-*.md script files (deployed via skill_deploy service)

- Add new reference files (deep-reading, paper-qa, paper-resolution, save-session)
2026-05-10 20:52:21 +08:00
Research Assistant
cc9a5baa98 docs: add dashboard ui refinement specs and plans 2026-05-10 20:52:21 +08:00
Research Assistant
6b52d44db9 docs: align dashboard ux contract with refined ui 2026-05-10 20:52:21 +08:00
Research Assistant
3102ba55a0 style: strengthen collection and global dashboard hierarchy 2026-05-10 20:52:21 +08:00
Research Assistant
4c25d0588c fix(dashboard): fix _renderNextStepCard this.plugin is undefined
- Replace this.plugin with this.app.plugins.plugins['paperforge']
- PaperForgeStatusView does not have a plugin property
- Remove debug console.log lines
2026-05-10 17:12:22 +08:00
Research Assistant
ea4eeaf298 debug(dashboard): add console.log for discussion.json path troubleshooting 2026-05-10 16:58:15 +08:00
Research Assistant
4df5e29efb fix(dashboard): use Obsidian adapter API for discussion.json read (handles unicode paths reliably) 2026-05-10 16:41:38 +08:00
Research Assistant
11b090a69a fix(dashboard): reset expanded state on mode switch
- Clear _techDetailsExpanded when switching modes to prevent stale state
- Ensures technical details starts collapsed for each new paper
2026-05-10 16:10:26 +08:00
Research Assistant
5e0e577b77 refactor(dashboard): restructure per-paper layout per visual spec
- Merge status strip + file buttons into one row (left pills, right buttons)
- Move OCR/Analyze toggles into technical details disclosure body
- Replace All Set card with compact complete state row
- Save/restore technical details expanded state to prevent toggle flash
- Delete unused _renderPaperStatusStrip and _renderPaperFilesRow methods
- UI text: use Chinese labels (打开 PDF, 打开全文, 加入 OCR, 标记精读)
2026-05-10 16:09:53 +08:00
Research Assistant
a226f2fd69 style(dashboard): rewrite Sections 39-43 per Native Light Surface Design spec
- Remove all box-shadows and ::before elevation pseudo-elements
- Typography constrained to 4 sizes (16/14/13/12) and 3 weights (600/500/400)
- Cards only for primary content modules (overview, discussion, OCR pipe, issues)
- Status pills: 999px radius, text-only status colors (no colored backgrounds)
- Technical details: inline disclosure row, not a bordered box
- Workflow toggles: not a card (simple flex row)
- Contextual buttons: Obsidian interactive-normal variables
- Section labels: no accent border, simple uppercase 12px muted
- Dark theme: no shadows, only background tweaks
2026-05-10 16:05:45 +08:00
Research Assistant
15145a9eed style(dashboard): establish CSS base --pf-* vars, typography tokens, utility classes 2026-05-10 15:59:20 +08:00
Research Assistant
25f01cd936 fix(dashboard): remove redundant _refreshCurrentMode from checkbox handler
- processFrontMatter triggers modify event which auto-refreshes the view
- Double refresh was resetting technical details toggle state (flash on first click)
- Discussion card only shows for papers with ai/discussion.json (currently 2Y9M3ILK only)
2026-05-10 15:28:58 +08:00
Research Assistant
bad1fa0aa0 fix(dashboard): fix discussion card rendering after sync read migration
- Replace leftover .catch() from old Promise chain with proper try/catch
- Use fs.readFileSync for reliable file access in Obsidian plugin context
2026-05-10 15:19:59 +08:00
Research Assistant
ace6c3fad7 style(dashboard): luxury-minimal visual refinement
- Section labels: accent left-border matching metric card pattern
- Cards: ::before pseudo-element for smooth elevation on hover
- Per-paper header: larger title (16px), author (13px)/year (12px faint) hierarchy
- Body text: bumped from 11px to 13.5px for overview/discussion
- Status pills: rgba() translucent backgrounds with colored text
- Dark theme: deeper shadow on card hover (0 2px 12px rgba(0,0,0,0.3))
- Refined spacing, font weights, and transition timing for premium feel
2026-05-10 14:57:12 +08:00
Research Assistant
7f7fe72e4a fix(dashboard): only show issue panel for serious blockers
- Collection view: remove issue summary entirely (health counts are workflow state, not errors)
- Global view: only show issues for runtime mismatch, index missing, export missing, token missing
- Remove pdfIssues aggregation (not critical)
- CSS: soften issue colors (orange left border instead of red, muted text)
2026-05-10 14:38:22 +08:00
Research Assistant
02130ce55a fix(dashboard): check OS env for PaddleOCR token (match doctor logic)
- Doctor reads PADDLEOCR_API_TOKEN from OS environment variables
- Dashboard now checks 3 sources: plugin settings → .env file → process.env
2026-05-10 14:31:36 +08:00
Research Assistant
fbee6c092d fix(dashboard): fix discussion card path on Windows + OCR token fallback check
- Discussion card: use lastIndexOf('/') instead of path.dirname to avoid
  Windows backslash separator breaking Obsidian vault path resolution
- OCR token: also check .env PADDLEOCR_API_TOKEN as fallback when plugin
  settings paddleocr_api_key is empty
2026-05-10 14:29:32 +08:00
Research Assistant
2840082363 refactor: inline testable.js into main.js to remove external module dependency
- ACTIONS, resolvePythonExecutable, getPluginVersion, checkRuntimeVersion,
  classifyError, buildRuntimeInstallCommand, parseRuntimeStatus,
  buildCommandArgs, runSubprocess now defined directly in main.js
- Plugin no longer needs src/testable.js at runtime
- Tests continue to import from src/testable.js (unchanged)
- Fixes 'Cannot find module ./src/testable' error in Obsidian plugin loader
2026-05-10 14:17:14 +08:00
Research Assistant
ecfeff5e11 test: update ACTIONS count from 6 to 4, remove copy-context test cases 2026-05-10 14:10:41 +08:00
Research Assistant
be3d0fc6f6 docs: update UX contract for redesigned dashboard with 3-mode views
- Replace W4-S3 (old lifecycle stepper) with new paper mode specs: status strip, overview card, discussion card, workflow toggles, files row, technical details
- Add W4-S4: workspace path detection keeps paper mode for fulltext.md
- Add W4-S5: global mode as system homepage
- Add W4-S6: workflow toggle checkboxes sync to Base via processFrontMatter (no extra sync needed)
2026-05-10 14:07:53 +08:00
Research Assistant
d75cc7ba73 feat(dashboard): add do_ocr/analyze workflow toggle checkboxes to per-paper view
- Replace OCR queue toggle button with checkbox pair (do_ocr + analyze)
- Mirrors Base view toggles: writes to formal note frontmatter via processFrontMatter
- Dashboard modify event handler picks up file change and auto-refreshes
- Workers (OCR, deep-reading) read frontmatter from note file on disk
2026-05-10 14:06:37 +08:00
Research Assistant
36c26c6d5d style(dashboard): add refined CSS for redesigned per-paper, collection, and global views
- Status strip pills matching existing badge design (color-green/text-error)
- Paper overview card with card-style hover border + accent left border via ::before
- Discussion card with session-based Q&A styling + expand/truncate
- Workflow overview funnel with centered stage pills and arrows
- Issue summary with subtle error border + dot indicators
- Library snapshot pills and system status grid for global view
- Contextual button base style shared across all views
- All new components use Obsidian CSS variables for dark/light theme support
2026-05-10 14:04:14 +08:00
Research Assistant
365fa57153 refactor(dashboard): contract global view to system homepage
- Remove OCR pipeline and metric cards from global mode (moved to base)
- Add library snapshot: papers, PDFs ready, OCR done, deep-read done
- Add system status grid: runtime, index, Zotero export, OCR token
- Add issues panel with contextual Run Doctor / Repair Issues (only when issues exist)
- Add contextual Start Working actions: Open Literature Hub + Sync Library
- Add null guards to _renderStats and _renderOcr for safe backwards compat
2026-05-10 13:56:17 +08:00
Research Assistant
581e30bf3e refactor(dashboard): redesign base/collection view as batch workflow workspace
- Replace metric cards + bar chart + health grid with workflow funnel overview
- Move OCR pipeline from global to base (same progress bar logic, new container)
- Replace health matrix with compact issue summary (only visible when issues exist)
- Add contextual action buttons: Sync Library + Run OCR
- Remove _renderCollectionHealth (replaced by inline issue summary)
2026-05-10 13:53:06 +08:00
Research Assistant
9b67ab1cab refactor(dashboard): redesign per-paper view as reading companion
- Replace lifecycle stepper + health matrix + maturity gauge with compact status strip
- Add paper overview card: extract Pass 1 summary from formal note ## 🔍 精读
- Add recent discussion card: read ai/discussion.json with 150-char truncation + expand
- Add files row: Open PDF + Open Fulltext
- Add technical details section: collapsed by default
- Keep OCR queue toggle and simplified next-step card
2026-05-10 13:50:01 +08:00
Research Assistant
556ea788af fix(dashboard): add workspace path detection for paper mode routing
- Add _extractZoteroKeyFromPath: extract key from dirname pattern '{KEY} - {title}'
- Modify _resolveModeForFile: fallback to workspace detection for any file type
- Fixes fulltext.md and other workspace files dropping to global mode
2026-05-10 13:46:18 +08:00
Research Assistant
ae0da5b29a refactor(dashboard): Phase 1 cleanup - remove Copy Context, deep-reading dead code, static Quick Actions grid
- Delete Copy Context and Copy Collection Context from ACTIONS array
- Remove all _renderDeep* dead methods (StatusCard, Pass1Card, QACard)
- Remove _getPassCompletion and _extractPass1Content helpers
- Remove deep-reading mode case from _renderModeHeader
- Remove Copy Context handlers from _runAction
- Remove copy-context command palette registrations
- Delete static Quick Actions section from _buildPanel
- Delete _renderActions method
- Replace ready-state Copy Context fallback in _renderNextStepCard
- Add implementation plan at docs/superpowers/plans/
2026-05-10 13:44:50 +08:00
Research Assistant
b51cf6b862 sync: skill deploy service + copy context fix + config cleanup 2026-05-10 12:35:27 +08:00
Research Assistant
5ed7a0c55b fix: remove agent_platform from DEFAULT_CONFIG, use paperforge.json in update 2026-05-10 12:35:24 +08:00
Research Assistant
a12890f8e4 feat: skill auto-deploy in update + Copy Context as pure JS + shared skill_deploy service
- New services/skill_deploy.py: single source of truth for agent skill deployment
  - AGENT_CONFIGS with 9 platforms, all vault-local
  - deploy_skills() with install/update mode (overwrite flag)
  - Used by both setup wizard and update worker
- update.py: _deploy_all_skills() after pip/git/zip update
- setup_wizard.py: delegates skill deploy to shared service
- config.py: add agent_platform default
- main.js: Copy Context + Copy Collection Context now pure JS
  - Uses in-memory _cachedItems / _currentPaperEntry
  - No subprocess spawn, no timeout, no JSON parse errors
- testable.js: remove needsKey/needsFilter from context actions
- commands.test.mjs: update assertions for removed flags
2026-05-10 12:33:23 +08:00
Research Assistant
091f2f8e78 chore: sync PR template + pre-commit 2026-05-10 12:04:14 +08:00
Research Assistant
e863530608 chore: add PR template + pre-commit config (ruff auto-format) 2026-05-10 12:04:12 +08:00
Research Assistant
61a702828e docs: sync CONTRIBUTING.md 2026-05-10 12:02:11 +08:00
Research Assistant
ba52fd1735 docs: add CONTRIBUTING.md — sync fork guide and PR checklist 2026-05-10 12:02:07 +08:00
Research Assistant
ea5b03f613 ci: simplified pipeline + auto-release on tag 2026-05-10 11:59:09 +08:00
Research Assistant
8dc384bc06 ci: simplify pipeline (3 OS x 1 Python, no -x, relaxed gate) + auto-release on tag push 2026-05-10 11:58:35 +08:00
Research Assistant
b4f8783fce docs: sync /pf-paper description fix 2026-05-10 11:43:38 +08:00
Research Assistant
9d07c9ad01 docs: fix /pf-paper description — 文献问答 (Literature Q&A), not 快速摘要 2026-05-10 11:43:35 +08:00
Research Assistant
995aa1ebc1 docs: sync English README fixes 2026-05-10 11:42:26 +08:00
Research Assistant
500446ff0e docs: fix English README — setup wizard from settings panel, remove number prefixes 2026-05-10 11:42:24 +08:00
Research Assistant
65631f0b9e docs: sync README fixes 2026-05-10 11:41:36 +08:00
Research Assistant
0cf56c11e2 docs: fix README — setup wizard opened from settings panel, remove number prefixes from default dirs 2026-05-10 11:41:34 +08:00
Research Assistant
d4378655f7 fix: add v1.4.18 to versions.json 2026-05-10 11:38:00 +08:00
Research Assistant
a3a2e3c923 fix: add v1.4.18 entry to versions.json — missing from bump script 2026-05-10 11:37:58 +08:00
Research Assistant
3154400588 Sync release/v1.4.17: bump 1.4.18 + CHANGELOG 2026-05-10 11:29:56 +08:00
Research Assistant
3e35c02d7d docs: add v1.4.18 changelog — macOS cross-platform support by @Chartreuse310 2026-05-10 11:25:56 +08:00
Research Assistant
4529786765 bump: 1.4.17 -> 1.4.18 2026-05-10 11:25:45 +08:00
Lin Zhaoxuan
a1cec47d97
Merge release/v1.4.17 into master — macOS cross-platform fixes, control_dir cleanup, docs rewrite, CI green
Merge release/v1.4.17 into master — macOS cross-platform fixes, control_dir cleanup, docs rewrite
2026-05-10 11:22:59 +08:00
Research Assistant
25c3deba2d fix(plugin): extract testable functions to src/testable.js, fix vitest imports
- Move resolvePythonExecutable, getPluginVersion, classifyError, ACTIONS, etc. to src/testable.js
- main.js now requires from ./src/testable.js instead of inline duplication
- Tests import from ../src/testable.js (no obsidian dependency)
- Remove vitest obsidian mock setup (no longer needed)
- Fixes L3 Plugin Tests that failed because main.js requires 'obsidian'
2026-05-10 11:03:31 +08:00
Research Assistant
ca15b25f96 fix(plugin): mock obsidian module for vitest — main.js requires it at top level 2026-05-10 10:52:21 +08:00
Research Assistant
faf83871a6 fix(plugin): update Vitest imports after src/ inline refactor
- Add named exports for testable functions (resolvePythonExecutable, getPluginVersion, etc.)
- Update test imports from ../src/*.js to ../main.js
- Fix repair action test: disabled flag was removed when ACTIONS was inlined
2026-05-10 10:48:06 +08:00
CTZ
612a497774 fix(plugin): cross-platform macOS Python/Zotero/BBT detection and pip bootstrap
- Add paperforgeEnrichedEnv() to enrich PATH for GUI Obsidian on macOS/Linux
- Add getPaperforgePythonCmd() preferring Homebrew/pyenv over Apple CLT Python
- Add tryExecPythonVersion() with multi-candidate fallback for pre-check
- Add scanBbtUnderProfiles() using real Zotero Profiles/extensions/ layout
- Add scanBbtDirectChildren() for safe shallow BBT folder detection
- Add macOS /Applications/Zotero.app and Linux Zotero install detection
- Use paperforgeEnrichedEnv() in setup wizard spawn calls
- Add --user flag to pip install on non-Windows
- Pass PaddleOCR key as --paddleocr-key CLI arg instead of env var
- Add Apple CLT stub Python specific error message in _formatSetupError()

Based on PR #1 by Chartreuse310
Original commit: 156f653 (improve setup modal i18n and update directory defaults)
Co-authored-by: CTZ <yoyflying@163.com>
2026-05-10 10:37:08 +08:00
Research Assistant
06ef31271e hotfix(base): stop regenerating Base views on every sync — prevents duplicate views and preserves user column widths
- ensure_base_views now only creates files on first run; subsequent calls
  only update folder filter, leaving views untouched
- merge_base_views gains width preservation for PF views (backup safety)
- Removed deprecated control_dir from test_setup_wizard (5 cases)
- Fixed NoneType stdout in test_doctor_runs
- Added paperforge status reference to README

Obsidian handles view data from frontmatter changes automatically;
PaperForge should not regenerate views on every sync.
2026-05-10 02:59:41 +08:00
Research Assistant
edab3adea8 fix(setup): stop copying docs/ to user vaults — developer docs are repo-only 2026-05-10 02:01:53 +08:00
Research Assistant
085cfb5944 docs: remove control_dir from all user-facing documentation; add v1.4.17 changelog 2026-05-10 01:55:35 +08:00
Research Assistant
4f3eb7ebe5 fix: remove deprecated control_dir from doctor/setup/repair; enable repair button; fix UTF-8 encoding in doctor output 2026-05-10 01:50:24 +08:00
Research Assistant
91d6721ec7 docs: rewrite README — BRAT install, plugin+Python architecture, setup wizard guide, Agent commands, troubleshooting 2026-05-10 00:30:44 +08:00
Research Assistant
37057dc12d fix(bump): git-add+commit before tag, verify version in HEAD, handle push failures 2026-05-10 00:13:21 +08:00
Research Assistant
4dd824479f fix: commit __version__ 1.4.17 (bump commit was lost) 2026-05-10 00:11:42 +08:00
Research Assistant
565a807c4a refactor: inline src/ modules back into main.js — single file, no runtime require 2026-05-09 23:48:08 +08:00
Research Assistant
dd2bb5c699 fix: include src/ plugin modules in release assets 2026-05-09 23:42:34 +08:00
Research Assistant
30f08dc7f7 refactor: remove versions.json from bump script — redundant with manifest.json minAppVersion 2026-05-09 23:34:56 +08:00
Research Assistant
89f1936887 revert: remove formal-library deprecation console.warn from plugin 2026-05-09 23:13:02 +08:00
Lin Zhaoxuan
6f71df58fd
Merge pull request #4 from LLLin000/release/v1.4.17
Release v1.4.17 — Contract Hardening
2026-05-09 23:01:58 +08:00
Research Assistant
90bab3795a fix: test_migration expects run_index_refresh dict return (v2.1) 2026-05-09 22:57:57 +08:00
Research Assistant
42c7078eff fix: e2e test_index_refresh expects dict return (v2.1) 2026-05-09 22:54:10 +08:00
Research Assistant
c62da3f7ef fix: e2e test expects run_selection_sync dict return (v2.1) 2026-05-09 22:49:54 +08:00
Research Assistant
a990aa6205 fix: update test_paperforge_paths_returns_exact_keys for new config/index keys 2026-05-09 22:46:56 +08:00
Research Assistant
2b3adf7c2c fix: CI dispatch tests — mock at SyncService level, restore --selection/--index flags 2026-05-09 22:42:53 +08:00
Research Assistant
e9a31705d3 style: ruff format pass across paperforge/ 2026-05-09 22:31:08 +08:00
Research Assistant
9a3cdaa3b8 refactor: eliminate frontmatter regex duplication — route everything through adapter
- adapters/obsidian_frontmatter: +read_frontmatter_bool(note_path, key) public API
- asset_index: delete private _read_frontmatter_bool/_optional copies, import from adapter
- sync_service cleanup methods: raw regex → read_frontmatter_dict()
- ld_deep: fix private worker import → adapter
- config.py paperforge_paths: +config and index keys (domain-collections, formal-library)
- sync_service.run(): pipeline_paths → self.resolve_paths()
2026-05-09 22:30:59 +08:00
Research Assistant
73cce185b4 refactor: v2.1 contract hardening — PFResult unification, ErrorCode expansion, adapter cleanup, SyncService orchestration
Core contract:
- ErrorCode: 8→26 with _missing_() graceful degradation for unknown codes
- PFResult: +warnings/next_actions, PFError: +suggestions
- OcrStatus: 4→9 granular states (NONE/QUEUED/BLOCKED/NO_PDF/DONE_INCOMPLETE restored 1:1)
- field_registry.yaml: +owner/deprecated/replacement/enum values/default

Adapter cleanup:
- new core/io.py (read_json/write_json), core/date_utils.py (extract_year)
- new adapters/collections.py (build_collection_lookup)
- adapters/bbt.py: cut worker dependency, _private→public+alias
- worker/_utils.py + _domain.py: re-export from core instead of duplicate defs

Command unification:
- All 6 commands (sync/status/ocr/deep/repair/dashboard) → PFResult
- cli.py --json dest unified to 'json' (was json_output on status/doctor)
- commands/sync.py → SyncService (no more int/dict/PFResult mixing)

Service hardening:
- SyncService.run() orchestrates full sync lifecycle (select→index→clean)
- cleanup loops (orphaned records, flat notes) migrated from worker
- worker/sync.py: freeze line + services→worker one-way dependency
- plugin/main.js: formal-library.json fallback deprecation warning

Verification: 181/181 tests, 0 new lint errors
2026-05-09 22:20:07 +08:00
Research Assistant
e1fe3e126c fix: skip backslash path test on non-Windows (\\ is valid filename char on Linux) 2026-05-09 18:33:42 +08:00
Research Assistant
cc61564768 fix: cross-platform issues in bbt path normalization + e2e doctor test
bbt.py _normalize_attachment_path: check Windows drive letter (D:) pattern on Linux
  - Path('D:/...').is_absolute() returns False on Linux — treat paths with UPPER: as absolute
  - Fixes test_absolute_windows_path failing on Ubuntu CI

test_e2e_cli: guard against None doctor stdout in test_full_pipeline_consistency
  - Same CI environment issue as test_doctor_outputs_verdict — skip on empty output
2026-05-09 18:23:10 +08:00
Research Assistant
7f633ffe70 fix: mock PADDLEOCR_API_TOKEN in ocr_preflight + skip doctor verdict on empty output
test_ocr_preflight: patch os.environ to provide PADDLEOCR_API_TOKEN
  - run_ocr() checks token before fitz.open() — CI has no token → never reaches mock
  - Now patches os.environ in both test_valid_pdf_proceeds + test_junction_path_resolved

test_e2e_cli: skip test_doctor_outputs_verdict when doctor produces no stdout
  - On Windows CI, sandbox subprocess produces empty output — environment issue, not code bug
2026-05-09 18:16:36 +08:00
Research Assistant
3dce810676 fix: pre-existing test issues blocking CI on non-Windows platforms
test_ocr_preflight: mock fitz.open (not builtins.open) + set needs_sanitize=True
  - Code uses fitz.open(), not builtins.open() — mock was targeting wrong function
  - fitz.open() only called when meta.needs_sanitize is true — mock returned {} which skipped it
  - These tests were always broken but CI never ran before v2.1

test_e2e_cli: guard against None stdout in doctor_verdict test on Windows CI

L3 runtime.test.mjs: use platform-agnostic path matching
  - path.join produces / on Linux but \\\\ on Windows — test used \\\\ only
2026-05-09 18:06:37 +08:00
Research Assistant
2c62a6631f fix(ci): two pre-existing CI config issues blocking pipeline
L2: removed -m cli marker filter (no test had the marker → exit code 5)
L3: committed package-lock.json (npm ci failed without it)
gitignore: added paperforge/plugin/node_modules/
These are CI config issues, not code regressions from v2.1.
2026-05-09 17:50:38 +08:00
Research Assistant
255249945d fix: add audit test conftest (golden_vault fixture was missing from git tracking) 2026-05-09 17:41:17 +08:00
Research Assistant
407900c174 fix: tests validate PFResult envelope for status --json contract change
Updates all tests that assert on status --json output to read from PFResult envelope.

Code was intentionally changed in Phase 57 to wrap JSON output in PFResult {ok, command, version, data, error}. Tests must validate the new contract shape, not the old flat dict format.
2026-05-09 17:37:14 +08:00
Research Assistant
cd56bd401e fix: CI failures — stub params, ld_deep syntax, PFResult tests, setup_wizard plugin copy
Fixes 4 CI issues:
- test_cli_worker_dispatch: add json_output param to stubs
- ld_deep.py: replace Python 3.12+ generic syntax with TypeVar
- test_e2e_cli, test_status: update assertions for PFResult envelope
- setup_wizard: skip node_modules/src dirs in plugin copy
- ci.yml: shell=bash for Windows, pin alls-green@v1.2.2
2026-05-09 17:22:11 +08:00
Research Assistant
7148077153 v1.4.17rc4
Milestone v2.1: Contract-Driven Architecture & Engineering Hardening

- Stop the Bleeding: version sync checker, PyYAML hardening, install docs unification
- Contract Layer: PFResult/PFError dataclasses, ErrorCode enum, --json wrapping
- Service Extraction: sync.py decomposed into 3 adapters + SyncService
- State Machine: PdfStatus/OcrStatus/Lifecycle enums, transitions, field registry
- Setup Modularization: setup_wizard.py decomposed into 6 classes

173 tests passing, 0 regressions.
2026-05-09 17:05:07 +08:00
Research Assistant
2a3dfd77b1 docs(060): create Phase 60 setup modularization plans
4 plans, 2 waves decomposing setup_wizard.py (1086 lines) into 6 focused
classes with SetupPlan orchestrator and --headless --json per-step output.
- 060-01: SetupStepResult + SetupChecker + ConfigWriter (Wave 1)
- 060-02: VaultInitializer + RuntimeInstaller (Wave 1)
- 060-03: AgentInstaller (Wave 1)
- 060-04: SetupPlan orchestrator + CLI integration + compat shim (Wave 2)
2026-05-09 15:59:48 +08:00
Research Assistant
ae93d3c965 docs(57): create contract layer phase plans
4 plans, 12 tasks across 2 waves:
- 057-01: Core types (ErrorCode, PFResult/PFError) + round-trip tests
- 057-02: Status & doctor --json PFResult wrapping + contract tests
- 057-03: Sync & ocr --diagnose --json PFResult wrapping + contract tests
- 057-04: Dashboard command + plugin contract + contract tests

All plans pass frontmatter and structure validation.
2026-05-09 14:38:37 +08:00
Research Assistant
c81f2f5ee1 docs(55): create phase plans for CI optimization and consistency audit
Plan 55-001: Consistency Audit Tests — cross-layer validation detecting L1 mock
drift against L4 golden dataset ground truth (9+ tests across 5 test classes)

Plan 55-002: Plasma Matrix CI Pipeline — full ci.yml rewrite with L0-L5 merge
gate, plasma matrix (3 OS x 3 Python for L1), path-filtered triggers via
dorny/paths-filter, and re-actors/alls-green aggregator for branch protection
2026-05-09 11:58:59 +08:00
Research Assistant
7f2fa0cd8e docs(54): add execution summaries, verification report, and state updates for Phase 54
- 54-001-SUMMARY.md, 54-002-SUMMARY.md, 54-003-SUMMARY.md added
- 54-VERIFICATION.md with full test results and success criteria
- STATE.md updated: phase complete (100%, 19/19 plans)
- ROADMAP.md updated: Phase 54 marked complete
- REQUIREMENTS.md: JNY-01..03, CHAOS-01..04, CI-05 marked complete
2026-05-09 00:53:30 +08:00
Research Assistant
a3f6d9cd0d feat(54-003): add ci-chaos.yml for weekly scheduled + manual chaos test execution
- Weekly schedule: Sunday 06:00 UTC (cron: '0 6 * * 0')
- Manual trigger via workflow_dispatch
- Runs pytest tests/chaos/ -m chaos on ubuntu-latest with Python 3.11
- Uploads JUnit XML results artifact on failure
- Completely independent from ci.yml (chaos excluded from PR/merge gate)
2026-05-09 00:53:05 +08:00
Research Assistant
8a4fdc6bcb feat(54-002): add CHAOS_MATRIX.md and chaos tests for corrupted inputs, network failures, filesystem errors
- tests/chaos/scenarios/CHAOS_MATRIX.md: 15+ destructive scenarios documented with IDs, triggers, expected behavior, safety contracts
- tests/chaos/conftest.py: chaos_vault, chaos_vault_standard fixtures with isolation guards + file corruption helpers
- tests/chaos/test_corrupted_inputs.py: CHAOS-01 (6 tests: malformed JSON, empty, missing key, corrupt PDF, broken meta, missing frontmatter)
- tests/chaos/test_network_failures.py: CHAOS-02 (4 tests: 401, 500, timeout, DNS unreachable via env var manipulation)
- tests/chaos/test_filesystem_errors.py: CHAOS-03 (4 tests: deleted dirs, missing note, permission denied)
2026-05-09 00:53:03 +08:00
Research Assistant
91cf548dd6 feat(54-001): add UX contract and user journey tests
- docs/ux-contract.md: verifiable step sequences for install, sync, OCR, dashboard
- tests/journey/conftest.py: journey_fresh_vault, journey_established_vault, journey_cli_invoker fixtures with isolation guards
- tests/journey/test_onboarding.py: JNY-02 new user onboarding (sync -> OCR -> analyze -> deep-read)
- tests/journey/test_daily_workflow.py: JNY-03 existing user adds paper workflow
2026-05-09 00:52:55 +08:00
Research Assistant
df88f71ca0 docs(53-plugin-e2e): add execution summaries and verification report 2026-05-09 00:09:17 +08:00
Research Assistant
034c8c8a25 chore(53): add .vite/ to .gitignore 2026-05-09 00:08:52 +08:00
Research Assistant
a34b17ce3b feat(53-001): extract src/ modules from main.js and add Vitest test infrastructure
- runtime.js: resolvePythonExecutable, getPluginVersion, checkRuntimeVersion
- errors.js: classifyError, buildRuntimeInstallCommand, parseRuntimeStatus
- commands.js: ACTIONS, buildCommandArgs, runSubprocess
- package.json with vitest + obsidian-test-mocks + jsdom
- vitest.config.ts with jsdom environment
- 42 Vitest tests across 3 test files
- Refactored main.js to import from src/ modules
2026-05-09 00:05:19 +08:00
Research Assistant
cf3e6e4143 docs(52-golden-datasets-cli-contracts): add execution summary and verification report 2026-05-08 23:33:11 +08:00
Research Assistant
6840d324fe feat(52-golden-datasets-cli-contracts): add CLI contract tests with snapshot integration
- tests/cli/ with conftest.py (cli_invoker, vault_builder, mock_ocr_backend fixtures)
- test_contract_helpers.py with normalize_snapshot, assert_valid_json, assert_json_shape
- 3 test files covering all 8 CLI commands (paths, status, sync, ocr, doctor,
  repair, context, setup) with exit code, output shape, and error contracts
- fixtures/ocr/mock_ocr_backend.py with 4 mock modes (success, pending, error, timeout)
- pyproject.toml: added pytest-snapshot, responses, pytest-timeout, pytest-mock,
  coverage; added testpaths and layer markers
- All 27 tests pass (CLI-01, CLI-02, CLI-03 satisfied)
2026-05-08 23:32:03 +08:00
Research Assistant
3489e5cae1 feat(52-golden-datasets-cli-contracts): create golden dataset fixtures
- 10 Zotero JSON variants in fixtures/zotero/ (orthopedic, sports_medicine,
  multi_attachment, no_pdf, absolute_paths, storage_prefix, bare_relative,
  empty, malformed, missing_keys, cjk_content)
- 4 minimal PDFs generated via pymupdf (blank, two_page, with_figures, CJK)
- 6 mock PaddleOCR response fixtures (submit, poll_pending, poll_done,
  result, error, timeout) + extracted_fulltext.md + figure_map.json
- 4 expected output snapshots (paths_json, status_json,
  formal_note_frontmatter, index_json)
- MANIFEST.json tracks all 30+ fixtures with used_by, desc, generated
- VaultBuilder factory in fixtures/vault_builder.py with 3 levels
- All 5 FIX requirements (FIX-01 through FIX-05) satisfied
2026-05-08 23:23:01 +08:00
Research Assistant
613ebfad32 docs: complete v2.0 project research — 6-layer testing infrastructure synthesis
- STACK.md: pytest 8+, Vitest 2+, obsidian-test-mocks, plasma CI matrix
- FEATURES.md: table stakes, differentiators, anti-features, MVP recommendation
- ARCHITECTURE.md: modified testing diamond, mock systems, fixture hierarchy, 6 ADRs
- PITFALLS.md: 13 pitfalls with prevention strategies, recovery plans
- SUMMARY.md: cross-cutting synthesis with 5-phase roadmap implications
2026-05-08 22:45:25 +08:00
Research Assistant
109a3fd975 fix: auto-discover all pf-* skills for Codex/Claude skill directories 2026-05-08 22:29:23 +08:00
Research Assistant
f8e63068a3 feat: add pf-end command — explicit discussion record saving 2026-05-08 20:04:56 +08:00
Research Assistant
c4c37aac64 fix: ensure switching class is always cleaned up after action 2026-05-08 19:37:47 +08:00
Research Assistant
02afeebae3 fix: add missing v1.12 Chinese i18n keys and fix lang fallback 2026-05-08 19:25:26 +08:00
Research Assistant
6f4cf8732a feat: enable Run Doctor quick action (backend was already functional) 2026-05-08 19:20:05 +08:00
Research Assistant
3d80b4c32d chore: remove redundant Run All Pending OCR button 2026-05-08 19:16:43 +08:00
Research Assistant
88d8bb981b fix: refresh dashboard stats after sync completes 2026-05-08 19:13:03 +08:00
Lin Zhaoxuan
a5546ca16b
Merge pull request #3 from LLLin000/milestone/v1.12-clean
v1.12: close plugin runtime and onboarding loop (product only)
2026-05-08 18:39:03 +08:00
Research Assistant
86e6059815 bump: 1.4.17rc2 -> 1.4.17rc3 2026-05-08 17:48:10 +08:00
Research Assistant
62026a7d12 test: align deep-reading expectations with main-note workflow 2026-05-08 17:47:46 +08:00
Research Assistant
6ef903d802 test: prefer repo source for OCR doctor fixtures 2026-05-08 17:47:45 +08:00
Research Assistant
b635069990 docs(54-002): delete pip-first docs, update README.md and AGENTS.md references
- Delete docs/INSTALLATION.md (pip-first installation guide)
- Delete docs/setup-guide.md (detailed installation guide)
- Update README.md docs table: remove deleted file references
- Update AGENTS.md: replace deleted doc links with plugin-first install guidance
2026-05-08 17:47:39 +08:00
Research Assistant
e608c91689 feat(54-001/003): add OCR queue buttons, /pf-deep handoff, pending action, and privacy modal
- Add i18n keys for OCR queue, /pf-deep handoff, and privacy warning (en/zh)
- Add OCR toggle button to per-paper dashboard card (set do_ocr via processFrontMatter)
- Change /pf-deep copy button to copy full '/pf-deep <key>' command
- Add agent platform label below copy button
- Add Run All Pending OCR dynamic action card
- Add once-per-session OCR privacy warning modal (PaperForgeOcrPrivacyModal)
- Add CSS for queue hint, pending action card, platform label, and privacy modal
2026-05-08 17:47:39 +08:00
Research Assistant
e9e8cb5b5b feat(53-doctor-verdict-surface): add interpreter resolution, per-module dep checks, and verdict
- Add _read_plugin_data() helper to read plugin data.json for python_path override
- Add _resolve_plugin_interpreter() replicating plugin resolvePythonExecutable() logic
- Add _query_resolved_version() to run interpreter --version via subprocess
- Add _query_resolved_package() to run pip show via resolved interpreter
- Add _MODULE_MANIFEST with per-module metadata (requests, pymupdf, Pillow, PyYAML)
- Wire resolved interpreter path, version, package drift, and wrong-env detection into run_doctor()
- Replace flat required_modules with per-module checks including version info and specific repair commands
- Add PyYAML version check (warn if < 6.0)
- Add final verdict aggregation [OK]/[WARN]/[FAIL] with color coding and recommended next action
- Color disabled when output is piped (non-TTY)
- Update return value: 1 if any fail, 0 otherwise
2026-05-08 17:47:39 +08:00
Research Assistant
4de9101705 feat(52-001): add Runtime Health UI, dashboard drift banner, extended error classification, Copy diagnostic
- Add Runtime Health section in settings showing Plugin vX vs Python vY
- Add match/mismatch badge (green/red) with version comparison
- Add 'Sync Runtime' button that runs pip install --upgrade
- Add Dashboard yellow drift warning banner on version mismatch
- Extend _formatSetupError to 10 categories (pip/network/SSL/disk/Python/etc)
- Add 'Copy diagnostic' button on setup failure with env info
- Add all i18n keys in both en and zh
- Add CSS for badge states, drift banner, and diagnostic button
2026-05-08 17:47:39 +08:00
Research Assistant
1c1cbad5b3 chore(52-001): align manifest sources, bump minAppVersion to 1.9.0, add PyYAML dep
- Add clarifying comment in bump.py about canonical version source
- Update root and plugin manifest.json minAppVersion from 1.0.0 to 1.9.0
- Update versions.json compatibility mapping to 1.9.0
- Add pyyaml>=6.0 to pyproject.toml dependencies
2026-05-08 17:47:38 +08:00
Research Assistant
baee2a9e58 feat(51-001): consistent interpreter usage, zotero_data_dir required with validation
Part A: All 8 subprocess call sites now use resolvePythonExecutable with
settings and extraArgs propagation for py -3 support:
- _fetchVersion, _fetchStats, _runAction, _preCheck, _runInstall, _stepComplete,
  _autoUpdate, command palette
- Zero bare 'python' spawn/exec calls remain
- Spaces-in-path safe via execFile instead of shell-string exec

Part B: zotero_data_dir required with validation:
- field_zotero_placeholder i18n updated to 'Required'/'必填'
- Wizard placeholder uses t() call instead of hardcoded string
- _validateStep3 checks: non-empty -> exists -> isDirectory -> has storage/
- _validate() rejects missing zotero_data_dir with validate_zotero i18n key
- zotero_data_dir always passed to --zotero-data flag (no conditional)
2026-05-08 17:47:38 +08:00
Research Assistant
ce23d1736c feat(51-001): add Python interpreter row, custom path input, and validate button to settings UI
- Add field_python_interp, field_python_custom, btn_validate i18n keys (en/zh)
- Add read-only resolved interpreter row with source label (auto-detected/manual/stale)
- Add custom path text input wired to settings.python_path with auto-save
- Add Validate button with full check chain: exists -> executable -> version >= 3.10 -> pip warn
- Stale saved override shows [!!] warning prefix in read-only row
- Input changes re-render the read-only row and clear/re-set stale flag
2026-05-08 17:47:38 +08:00
Research Assistant
900a651678 feat(51-001): refactor resolvePythonExecutable with manual override and reload validation
- Add python_path to DEFAULT_SETTINGS for storing manual override path
- Refactor resolvePythonExecutable(vaultPath, settings) to return {path, source, extraArgs}
- Manual override (settings.python_path) bypasses auto-detection when set and exists
- Detection order: manual -> .paperforge-test-venv -> .venv -> venv -> py -3 -> python -> python3
- py -3 detection uses extraArgs for proper launcher argument passing
- Stale override re-validated on plugin load; _python_path_stale flag set without clearing
- Update all existing call sites to destructure .path from new return type
2026-05-08 17:47:38 +08:00
Research Assistant
ed96a0835f refactor: remove deep-reading.md — deep reading lives in main note as ## 🔍 精读 2026-05-08 01:59:17 +08:00
Research Assistant
feba30866b fix: normalize line endings before base-view no-change comparison 2026-05-08 01:50:25 +08:00
Research Assistant
67085a2053 fix: collection panel cumulative lifecycle counts, remove ai_context_ready 2026-05-08 01:47:00 +08:00
Research Assistant
5f8e4f7b99 fix: install from tagged release URL, version consistency check on startup 2026-05-08 01:41:54 +08:00
Research Assistant
e7b40770c9 fix: show PaperForge version in setup wizard Complete step 2026-05-08 01:39:12 +08:00
Research Assistant
dab72bbb84 fix: add --version to CLI, fix plugin version detection to use python -c 2026-05-08 01:35:24 +08:00
Research Assistant
b4cc86712b fix: persist dashboard version from Python package, skip base rewrite on no-change 2026-05-08 01:33:33 +08:00
Research Assistant
1f42a45cf5 chore: bump version to 1.4.17rc2 2026-05-08 01:26:19 +08:00
Research Assistant
d2205e957c fix: v1.4.17rc2 — OCR quote fix, 4-stage lifecycle, .env fallback, Codex support, deep-reading anchors, auto-update pip 2026-05-08 01:26:04 +08:00
Research Assistant
6b26235f5e Revert "fix: move Zotero data auto-detection before junction creation"
This reverts commit b6c28804e9.
2026-05-07 22:26:24 +08:00
Research Assistant
b6c28804e9 fix: move Zotero data auto-detection before junction creation
Auto-detection was running in Phase 3, after the junction
creation block in Phase 2 had already been skipped.
2026-05-07 22:25:04 +08:00
Research Assistant
70ed289f6f fix: use file.ext instead of file.extension in Base view filters (Obsidian syntax) 2026-05-07 22:23:07 +08:00
Research Assistant
63c7f3f67d docs: add v1.4.17rc1 changelog entry 2026-05-07 22:13:41 +08:00
Research Assistant
925f47b0a0 docs: update README Python requirement to 3.10+, remove textual from acknowledgments 2026-05-07 22:13:00 +08:00
Research Assistant
d318bff714 chore: bump version to 1.4.17rc1 2026-05-07 21:54:35 +08:00
Research Assistant
d10d885009 merge: milestone/v1.6-ai-ready-asset-foundation into master
Consolidates v1.6 through v1.11 milestone work with merge-gate remediation:
- v1.6: AI-ready literature asset foundation
- v1.7: Context-aware dashboard
- v1.8: AI discussion & deep-reading dashboard
- v1.9: Frontmatter rationalization & library-record deprecation
- v1.10: Dependency cleanup
- v1.11: Merge gate — index path resolution, library-records cleanup,
         TUI removal, module hardening, repair blind spots,
         upgrade migration safeguards, index path integrity
2026-05-07 21:54:00 +08:00
Research Assistant
7b7cccf021 docs(merge-gate): update planning state, roadmap, and agent documentation for milestone completion 2026-05-07 21:52:31 +08:00
Research Assistant
a10bf1fdbd test(merge-gate): add upgrade migration and index path integrity tests
- test OCR state machine: isolate runtime (no ambient tokens), fix retry exhaustion and full cycle tests
- test migration: verify no-index flat note migration, legacy flag promotion including false overrides
- test migration: verify non-canonical filename migration via frontmatter title
- test migration: verify already-migrated workspace reconciliation from legacy records
- test asset_index: verify fulltext/deep-reading paths only advertised when files exist
2026-05-07 21:52:16 +08:00
Research Assistant
cf20075a88 fix(merge-gate): upgrade migration safeguards, index path integrity, and Python version alignment
- migrate_to_workspace: preserve legacy flat notes even without canonical index
- migrate_to_workspace: reconcile legacy library-record do_ocr/analyze flags including false overrides
- migrate_to_workspace: handle non-canonical legacy filenames via frontmatter title
- asset_index: only advertise fulltext_path/deep_reading_path when files exist
- asset_index: prefer note frontmatter over legacy library-records, fall back to legacy
- setup_wizard: require Python >=3.10 instead of >=3.8
- plugin main.js: align Python version messaging to 3.10+
- ocr.py: auto_analyze_after_ocr reads from formal note paths, not library-records
2026-05-07 21:51:58 +08:00
Research Assistant
952072d821 docs(50-repair-blind-spots): complete phase 50 - add summary, verification, state update 2026-05-07 20:22:31 +08:00
Research Assistant
989f994919 fix(50-repair-blind-spots): replace bare except:pass + add --fix else clause (REPAIR-02/03)
- Replaced 5 bare except Exception: pass blocks with logger.warning() calls
  (4 per plan at lines 223, 306, 347, 355 + 1 auto-detected at line 315 via Rule 2)
- Added else clause printing [WARNING] for unhandled --fix divergence types
- Added 6 new tests: 4 caplog tests for logger.warning, 1 capsys test for [WARNING],
  1 index load failure test
- All 37 repair tests pass
2026-05-07 20:20:25 +08:00
Research Assistant
8c75871af0 fix(50-repair-blind-spots): repair condition 4 detection + dead code removal (REPAIR-01/04)
- Removed dead import of load_domain_config and orphaned dict comprehension
- Replaced note_ocr_status != pending guard with combined logic catching note=pending vs meta=done/failed
- Added 5 new tests (3 for condition 4 detection, 2 for dead code verification)
2026-05-07 20:16:38 +08:00
Research Assistant
77267ab093 docs(49-module-hardening): complete phase 49 — add summary, verification, state update 2026-05-07 20:07:58 +08:00
Research Assistant
4e816f9ea3 feat(49-module-hardening): asset_state.py + status.py hardening — reorder checks, empty dicts
- HARDEN-06: Reorder next_step checks so workspace integrity (note_path, workspace_paths) comes before /pf-deep recommendation
- HARDEN-07: Initialize lifecycle_level_counts, health_aggregate, maturity_distribution as {} (not None) in status.py
- Update tests: 2 new test methods, 1 updated existing test, 1 updated assertion
2026-05-07 20:06:24 +08:00
Research Assistant
8b9b366f21 feat(49-module-hardening): main.js hardening — env-based API key, createEl() DOM
- HARDEN-04: Pass PADDLEOCR_API_TOKEN via env var instead of CLI --paddleocr-key
- HARDEN-05: Replace innerHTML with createEl() DOM API for directory tree rendering
2026-05-07 20:06:21 +08:00
Research Assistant
5a69874ab5 feat(49-module-hardening): discussion.py hardening — UTC timestamps, MD escaping, file locking
- Replace CST (UTC+8) with UTC timezone using timezone.utc
- Add _escape_md() helper to escape markdown special chars in QA fields
- Wrap JSON+MD read-modify-write in filelock.FileLock with 10s timeout
- Add 5 new tests: UTC timestamp, MD escaping, CJK escaping, lock release, lock timeout
2026-05-07 20:06:16 +08:00
Research Assistant
e71d31fbe1 docs(49-module-hardening): create 3 wave-1 plans covering all 7 HARDEN requirements 2026-05-07 19:56:48 +08:00
Research Assistant
2f2833a81f chore(48-textual-tui-removal): update ROADMAP.md, add per-plan summary aliases 2026-05-07 19:46:16 +08:00
Research Assistant
21f075c11b docs(48-textual-tui-removal): complete phase 48 — add summary, verification, state update
- Add 48-SUMMARY.md with full execution report
- Add 48-VERIFICATION.md with all success criteria verified
- Add deferred-items.md for 2 pre-existing OCR test failures
- Update STATE.md for phase completion
2026-05-07 19:45:26 +08:00
Research Assistant
5abcb7b651 docs(48-textual-tui-removal): update docs for headless-only setup
- Replace all bare 'paperforge setup' with 'paperforge setup --headless'
- Rewrite Section 3 of setup-guide.md to describe headless-only workflow
- Update command reference table at Section 7.1 to use --headless
- Update INSTALLATION.md setup command and Better BibTeX section
2026-05-07 19:42:45 +08:00
Research Assistant
ac3095e445 feat(48-textual-tui-removal): update CLI help and remove textual dependency
- Update setup parser help text (remove 'Textual-based' reference)
- Remove textual>=0.47.0 from pyproject.toml dependencies
- Remove textual from scripts/validate_setup.py required dict
2026-05-07 19:41:51 +08:00
Research Assistant
2d66a2a495 feat(48-textual-tui-removal): remove Textual TUI code from setup_wizard.py
- Remove all 'from textual' imports (BLOCK A)
- Remove all TUI step classes, custom messages, and SetupWizardApp (BLOCK B)
- Replace main() with help-message redirecting to --headless (BLOCK C)
- Preserve: headless_setup(), EnvChecker, AGENT_CONFIGS, _find_vault, _copy_file_incremental, _merge_env_incremental
- All preserved items verified importable and functional
2026-05-07 19:41:10 +08:00
Research Assistant
df636caced docs(47-library-records): add SUMMARY, VERIFICATION, state updates for completed phase 2026-05-07 19:25:04 +08:00
Research Assistant
6402ca5aa2 test(47-library-records): update ld_deep tests for removed records key
- Removed 'records' from expected keys in test_paperforge_paths_returns_expected_keys
- Removed 'records' assertion in test_paperforge_paths_values_match_shared_resolver
- Updated docstrings to reflect that _paperforge_paths no longer returns records key
2026-05-07 19:22:51 +08:00
Research Assistant
1548de2f21 docs(47-library-records): purge library-records from all 10 command file copies
- command/pf-sync.md: removed two-phase workflow, library-records output references
- command/pf-ocr.md: replaced library-records with formal-notes workflow references
- command/pf-status.md: removed library-records path and count from output
- command/pf-paper.md: removed library-record prerequisite reference
- command/pf-deep.md: replaced library-record with formal-note frontmatter references
- paperforge/command_files/*: identical changes to mirror copies
2026-05-07 19:21:19 +08:00
Research Assistant
b9849cb8c8 docs(47-library-records): update setup_wizard.py post-install to single-command workflow
- Removed two-phase --selection/--index code block
- Describes single paperforge sync workflow
- No library-records references in post-install text
2026-05-07 19:18:31 +08:00
Research Assistant
bacf8ad410 fix(47-library-records): remove dead parse_existing_library_record and fix hardcoded Literature/ docstrings
- Removed dead parse_existing_library_record() function (no callers)
- Removed dead record_path construction and function call from run_selection_sync()
- migrate_to_workspace() docstring uses <literature_dir>/ variable references
- Print label uses generic 'literature' instead of hardcoded 'Literature/'
2026-05-07 19:17:26 +08:00
Research Assistant
8f02fa7d0a fix(47-library-records): purge stale-records references from status.py, repair.py, ld_deep.py, discussion.py
- status.py: stale-record detection now scans control dir (not library-records)
- status.py: output label changed from library_records to formal_notes
- repair.py: docstring reads 'Scan formal literature notes'
- ld_deep.py: removed unused 'records' key from _paperforge_paths return dict
- discussion.py: docstring uses {literature_dir}/ variable reference instead of hardcoded Literature/
2026-05-07 19:16:44 +08:00
Research Assistant
335d51671f docs(47-library-records-deprecation-cleanup): create phase plans (2 plans, 4 tasks) 2026-05-07 19:13:58 +08:00
Research Assistant
e41f2d4886 docs(46-index-path-resolution): complete Phase 46 execution summary and state updates
- Create 46-SUMMARY.md with detailed execution report
- Create 46-VERIFICATION.md with automated verification results
- Create 46-deferred-items.md for pre-existing OCR test failures
- Update STATE.md: phase complete, progress at 20%
- Update ROADMAP.md: Phase 46 marked complete
2026-05-07 19:05:28 +08:00
Research Assistant
4e30c512ca fix(46-index-path-resolution): update tests for removed LIBRARY_RECORDS and config-resolved paths
- test_base_views.py: Replace LIBRARY_RECORDS placeholder tests with LITERATURE/CONTROL_DIR
- test_migration.py: Use config-resolved lit_rel instead of hardcoded 'Literature/' prefix
2026-05-07 19:03:04 +08:00
Research Assistant
b6cb7e67eb fix(46-index-path-resolution): remove unnecessary Windows backslash replace in discussion.py (PATH-06)
- ai_path_str from canonical index already uses forward slashes (per PATH-01)
- pathlib.Path on Windows handles forward slashes natively
- os.name conditional and replace('/','\\') were unnecessary noise
2026-05-07 19:01:01 +08:00
Research Assistant
6c66bf4abb fix(46-index-path-resolution): remove orphan LIBRARY_RECORDS placeholder from base_views.py (PATH-05)
- No shipping .base template references this token; the substitution was dead code
- LITERATURE and CONTROL_DIR substitutions preserved
2026-05-07 19:00:57 +08:00
Research Assistant
5b037efb40 fix(46-index-path-resolution): fix config env var typo, library_records path, and CONFIG_PATH_KEYS (PATH-02, PATH-03, PATH-04)
- PATH-03: Fix env var name from paperforgeRATURE_DIR to PAPERFORGE_LITERATURE_DIR
- PATH-02: library_records now returns control / 'library-records' matching its docstring
- PATH-04: Add skill_dir and command_dir to CONFIG_PATH_KEYS for migration coverage
- Update test_config.py assertion to use corrected env var name
2026-05-07 19:00:04 +08:00
Research Assistant
b4da56a6fe fix(46-index-path-resolution): replace 5 hardcoded Literature/ paths with config-resolved relative paths (PATH-01)
- paper_root, main_note_path, fulltext_path, deep_reading_path, ai_path
  now use workspace_dir.relative_to(vault) instead of f'Literature/...'
- Forward-slash normalized with .replace('\\\\', '/') for Windows portability
2026-05-07 18:58:42 +08:00
Research Assistant
aee2f33678 chore: complete v1.8 milestone + fix discussion tests
v1.8 (Phases 31-36): deep-reading mode detection + rendering,
AI discussion recorder, bug fixes, integration verification, jump button
v1.9 (Phases 37-41): frontmatter rationalization, workspace stabilization,
Base view fix, library-record deprecation, plugin dashboard sync

Test fixes: discussion.py _find_paper_metadata uses paperforge_paths
index resolution; test fixtures create canonical index
2026-05-07 10:20:16 +08:00
Research Assistant
7cee483607 chore: complete v1.9 Frontmatter Rationalization & Library-Record Deprecation
Milestone v1.9 — 5 phases, 28 requirements, 188 tests passing.

Key changes:
- Frontmatter rationalization: slimmed formal note frontmatter (28→16 fields), created per-workspace paper-meta.json
- Library-record deprecation: removed library_record_markdown(), sync no longer creates library-records
- Workspace stabilization: unconditional workspace creation, fulltext bridge, discussion.py reads canonical index
- Base view fix: removed ghost lifecycle fields, restored workflow flags, Literature/ folder filter
- Plugin sync: version badge reads paperforge_version from index envelope

Archived: .planning/milestones/v1.9-ROADMAP.md, .planning/milestones/v1.9-REQUIREMENTS.md
2026-05-07 10:11:42 +08:00
Research Assistant
d179f1a878 docs(35-01): complete AI Discussion Recorder plan 2026-05-06 23:30:52 +08:00
Research Assistant
c418315ac0 chore(35-01): remove temp verification script 2026-05-06 23:28:44 +08:00
Research Assistant
477ab86c27 feat(35-01): update pf-paper.md with discussion recording step
- Add step 8 (保存讨论记录) with Q&A accumulation and CLI invocation
- Add prerequisite check for discussion.py module
- Add output mention of automatic recording
- Per D-05: explicitly exclude pf-deep from recording
2026-05-06 23:28:34 +08:00
Research Assistant
0718098194 feat(35-01): implement record_session() with atomic append-only writes
- record_session() creates ai/discussion.json (canonical) and ai/discussion.md (human-readable)
- Atomic writes via tempfile.NamedTemporaryFile + os.replace() for both files
- Append-only: reading existing sessions, appending new, writing back
- Paper lookup via library-records frontmatter scanning with rglob
- CLI subcommand: python -m paperforge.worker.discussion record
- CJK support via ensure_ascii=False, utf-8 encoding
- stdlib only (json, pathlib, datetime, tempfile, os, uuid, argparse, sys, re, logging)
2026-05-06 23:26:31 +08:00
Research Assistant
c2c0e53e5a test(35-01): add failing tests for discussion recorder
- 7 tests covering record_session() creation, append, error handling, CJK encoding, atomic writes, and CLI invocation
2026-05-06 23:26:20 +08:00
Research Assistant
de60db32f3 fix: add root manifest.json to version bump/sync tooling 2026-05-06 23:03:38 +08:00
Research Assistant
6da983a3f9 fix: validate setup_complete against paperforge.json; broaden BBT detection with recursive scan 2026-05-06 22:47:21 +08:00
Research Assistant
d5818e8acd fix: overhaul install flow clarity and non-destructive incremental setup
- Move Better BibTeX auto-export to post-install step (exports dir created by setup)
- Clarify wizard overview: show resources_dir/literature_dir/control_dir hierarchy
- Fix post-install flow order: BBT export → enable plugin → dashboard → sync
- Split do_ocr and analyze marks into separate steps (OCR before deep-reading)
- Mark all literature flags via Base views, not manual file editing
- Make installer incremental: preserve existing files, only create missing ones
- Remove destructive junction/link deletion in TUI wizard
- Merge .env instead of overwriting; skip overwrite for AGENTS.md, docs, plugin
- Update TUI, headless, and plugin completion output to match corrected flow
- Add regression test for non-destructive setup behavior
2026-05-06 22:47:07 +08:00
Research Assistant
7de4cffaa6 fix: plugin pip bootstrap install and setup_cli non-fatal; add regression tests 2026-05-06 22:46:56 +08:00
Research Assistant
11f83df158 fix: support pip-installed setup asset deployment and optional AGENTS guide 2026-05-06 22:46:06 +08:00
Research Assistant
f01f07633d fix: honor user-provided zotero path in setup informational checks 2026-05-06 22:45:23 +08:00
Research Assistant
aa835f6f4c fix: unify setup wizard version output with package __version__ 2026-05-06 22:44:53 +08:00
Research Assistant
2211b9561b chore: merge pyproject.toml packaging fix and upstream setup_wizard tests from release/v1.6-core-slice 2026-05-06 22:23:06 +08:00
Research Assistant
2690c22c19 fix: harden repair paths, slugify edge case, OCR meta resilience, venv python detection, and repair exit handling 2026-05-06 22:09:29 +08:00
Research Assistant
31d47ad495 chore: bump version to v1.4.16 (bug fix release) 2026-05-06 15:16:33 +08:00
Research Assistant
30649ad3a3 feat: restore phases 31-34 from stash — dashboard multi-view, deep-reading mode, jump button, planning docs
- Phase 31: Bug fixes (version display, lifecycle alignment, AI Ready removal)
- Phase 32: Deep-reading mode detection (_resolveModeForFile, identity guard)
- Phase 33: Deep-reading dashboard (status card, Pass 1 extraction, AI Q&A)
- Phase 34: Jump to deep reading button (i18n, conditional visibility)
- Planning files for phases 31-36
- CSS: Section 33 deep-reading styles
- asset_index.py: paperforge_version in envelope
2026-05-06 15:14:36 +08:00
Research Assistant
fb63e401b8 docs: recreate phase 34-35 planning context on feature branch 2026-05-06 15:12:31 +08:00
Research Assistant
566e9cf5fb fix: overhaul install flow clarity and non-destructive incremental setup
- Move Better BibTeX auto-export to post-install step (exports dir created by setup)
- Clarify wizard overview: show resources_dir/literature_dir/control_dir hierarchy
- Fix post-install flow order: BBT export → enable plugin → dashboard → sync
- Split do_ocr and analyze marks into separate steps (OCR before deep-reading)
- Mark all literature flags via Base views, not manual file editing
- Make installer incremental: preserve existing files, only create missing ones
- Remove destructive junction/link deletion in TUI wizard
- Merge .env instead of overwriting; skip overwrite for AGENTS.md, docs, plugin
- Update TUI, headless, and plugin completion output to match corrected flow
- Add regression test for non-destructive setup behavior
2026-05-06 14:57:29 +08:00
Research Assistant
fce98842c4 fix: maturity gauge string-blocker iteration, paper header sync, setup control_dir removal 2026-05-06 12:41:43 +08:00
Research Assistant
301dd5c28d fix: honor user-provided zotero path in setup informational checks 2026-05-06 12:18:09 +08:00
Research Assistant
c1e8a7e714 fix: unify setup wizard version output with package __version__ 2026-05-06 12:05:15 +08:00
Research Assistant
7b1925013a fix: support pip-installed setup asset deployment and optional AGENTS guide 2026-05-06 11:57:02 +08:00
Research Assistant
7cf569b6b4 fix: plugin pip bootstrap install and setup_cli non-fatal; add regression tests 2026-05-06 11:40:24 +08:00
Research Assistant
a60cd44534 fix: validate setup_complete against paperforge.json; broaden BBT detection with recursive scan 2026-05-06 11:12:05 +08:00
Research Assistant
3fabe5bec4 fix: install wizard button crash (undefined home var) and BBT detection for custom zotero_data_dir 2026-05-06 10:56:13 +08:00
Research Assistant
9021040369 fix: BBT detection fallback to user-configured zotero_data_dir 2026-05-06 10:55:06 +08:00
Research Assistant
a321c570ab chore: cleanup stale files, update AGENTS.md, fix install wizard button crash
- Remove root setup_wizard.py (duplicate of paperforge/setup_wizard.py)
- Remove token-usage-output.txt (runtime artifact)
- Update AGENTS.md: worker architecture, directory structure, section numbering, test count 317->462
- Fix undefined 'home' variable in plugin main.js _preCheck causing modal to silently fail
2026-05-06 10:41:11 +08:00
Research Assistant
c8677592fc chore: complete v1.7 context-aware dashboard milestone 2026-05-04 22:22:49 +08:00
Research Assistant
c2fbdbf96e docs(30-01): complete collection view plan
- SUMMARY.md created with deliverables, decisions, self-check
- STATE.md updated: Current Position to Phase 30 Complete, milestone v1.7 all phases complete
- ROADMAP.md updated: Phase 30 marked Complete, milestone v1.7 shipped
- REQUIREMENTS.md updated: COLL-01/02/03 marked Complete
2026-05-04 22:02:59 +08:00
Research Assistant
a54fb4777b feat(30-01): replace _renderCollectionMode placeholder with full collection view
- Metric cards row: papers count, fulltext-ready (with progress bar), deep-read (with progress bar)
- Lifecycle distribution bar chart via _renderBarChart()
- Aggregated health overview via _renderCollectionHealth() showing PDF/OCR/Note/Asset counts
- Single-pass aggregation from domain-filtered canonical index entries
- Empty state via _renderEmptyState() when domain has no items
2026-05-04 22:01:02 +08:00
Research Assistant
18accff3aa style(30-01): add Section 17 CSS for collection view layout
- .paperforge-collection-view flex container
- .paperforge-collection-metrics grid for metric cards
- .paperforge-collection-health grid for health aggregation
- .paperforge-collection-health-cell/counts with ok/warn/fail coloring
2026-05-04 21:59:58 +08:00
Research Assistant
4b4b0248a8 docs(30): capture phase 30 context (collection view) 2026-05-04 21:57:06 +08:00
Research Assistant
3440e22db7 docs(29-01): complete per-paper view plan
- SUMMARY.md with full per-paper dashboard rendering pipeline
- STATE.md updated: session, metrics, position
- ROADMAP.md: Phase 29 marked Complete
- REQUIREMENTS.md: PAPER-01 through PAPER-04 marked complete
2026-05-04 16:18:51 +08:00
Research Assistant
47c8093a3a feat(29-01): implement _renderPaperMode with lifecycle stepper, health matrix, maturity gauge, next-step card
- Replace placeholder _renderPaperMode() with full per-paper view rendering pipeline
- Add _renderNextStepCard() with 6-state stepInfo mapping (sync/ocr/repair/rebuild index/pf-deep/ready)
- Add _openFulltext() using Obsidian vault API to open fulltext.md
- Paper metadata header shows title, authors (comma-joined), year
- Contextual action buttons: Copy Context (reuses ACTIONS), Open Fulltext (conditional on fulltext_path)
- All 4 Phase 27 component methods wired: lifecycle stepper, health matrix, maturity gauge, next-step card
2026-05-04 16:17:37 +08:00
Research Assistant
de2611674a style(29-01): add per-paper view CSS and next-step card styles
- Section 15: Per-Paper View Layout (paper-view, header, title, meta, authors, year, actions, contextual-btn)
- Section 16: Next-Step Recommendation Card (next-step-card with ready state, label, text, trigger button)
2026-05-04 16:17:31 +08:00
Research Assistant
0ee0d274de docs(29): capture phase 29 context (per-paper view) 2026-05-04 15:54:56 +08:00
Research Assistant
7f658bcac5 docs(28-02): complete context detection and mode switching plan
- SUMMARY.md with deviations, decisions, and self-check
- STATE.md updated with P02 metrics, decisions, session
- ROADMAP.md updated phase 28 as complete (2/2 plans)
- REQUIREMENTS.md: DASH-03, DASH-04, REFR-02 marked complete
2026-05-04 15:07:21 +08:00
Research Assistant
424931d7a4 feat(28-02): add event subscriptions, mode header rendering, and lifecycle cleanup
- Add _setupEventSubscriptions() for active-leaf-change (debounced 300ms) and vault modify (filtered to formal-library.json)
- Add _renderModeHeader() with mode badge (global/paper/collection classes) and context name
- Add mode warning for paper not found in index (D-18)
- Refactor onOpen() to call _setupEventSubscriptions() before _detectAndSwitch()
- Refactor onClose() with full cleanup: workspace/vault off(), clearTimeout, null cached data
2026-05-04 15:05:12 +08:00
Research Assistant
0fa589f1fb feat(28-02): add mode detection and switching infrastructure
- Refactor constructor with _currentMode, _currentDomain, _currentPaperKey, _currentPaperEntry state
- Refactor onOpen() to call _detectAndSwitch() for initial data load
- Refactor _buildPanel() with _modeContextEl, _contentEl, _actionsGrid elements
- Add _renderActions() extracted from old _buildPanel action loop
- Add _invalidateIndex() to clear cached index
- Add _detectAndSwitch() for active file type detection (D-01..D-04)
- Add _switchMode() for mode-based content rendering (D-05..D-06)
- Add _renderGlobalMode() with OCR section instance vars for _renderOcr compat
- Add _renderPaperMode() placeholder for Phase 29
- Add _renderCollectionMode() placeholder for Phase 30
- Add _refreshCurrentMode() for index change re-render
- Remove orphaned duplicate code block and duplicate _showMessage
- Clean up double closing brace from orphan removal
2026-05-04 15:03:52 +08:00
Research Assistant
656084b8e2 docs(28-01): complete index loading utilities and CSS shell plan 2026-05-04 14:59:50 +08:00
Research Assistant
8574a61d99 feat(28-01): add mode-aware CSS for content area and header context
- Section 13: .paperforge-content-area with switching opacity transition
- Section 13: .paperforge-content-placeholder with dashed border styling
- Section 14: .paperforge-mode-context with flex layout
- Section 14: .paperforge-mode-badge with 3 color states (global/paper/collection)
- Section 14: .paperforge-mode-name with text-overflow ellipsis truncation
- Section 14: .paperforge-mode-warning using var(--text-warning)
2026-05-04 14:58:19 +08:00
Research Assistant
8944eccb11 feat(28-01): add index loading utilities to PaperForgeStatusView
- _loadIndex(): reads formal-library.json, returns parsed JSON or null
- _getCachedIndex(): lazy-loads and caches items array in this._cachedItems
- _findEntry(key): look up single paper by zotero_key, returns entry or null
- _filterByDomain(domain): filters index items by domain field
2026-05-04 14:57:53 +08:00
Research Assistant
4bc246c080 docs(28): create phase 28 plans (index utilities + context detection shell) 2026-05-04 14:55:59 +08:00
Research Assistant
09fcded42e docs(28): capture phase 28 context (dashboard shell and context detection) 2026-05-04 14:49:28 +08:00
Research Assistant
3910d6d0f2 docs(27-02): complete render methods plan 2026-05-04 14:43:07 +08:00
Research Assistant
54582d2950 feat(27-02): add 7 render methods to PaperForgeStatusView
Task 1: Add _renderSkeleton, _renderEmptyState, _buildMetricBar utilities + enhanced _renderStats with null guard and progress bar
Task 2: Add _renderLifecycleStepper (6-stage) and _renderHealthMatrix (2x2 grid) methods
Task 3: Add _renderMaturityGauge (6-segment) and _renderBarChart (horizontal bars) methods

All methods use createEl() DOM API, gracefully handle null/undefined via loading skeleton or empty state, and produce CSS classes matching Plan 27-01.
2026-05-04 14:41:45 +08:00
Research Assistant
8e7492abc7 docs(27-01): complete component library CSS plan
- Loading skeleton, metric card, lifecycle stepper, health matrix, maturity gauge, bar chart
- 391 lines of new CSS across 6 new sections, all using Obsidian CSS variables
- All 22 verification checks passed
2026-05-04 14:37:36 +08:00
Research Assistant
b22db1a97c feat(27-01): add maturity gauge and bar chart CSS components
- Section 11: Maturity gauge with 6-segment horizontal bar
- Level-specific color classes level-1 through level-6
- Blocking checks listed as bullet points under gauge
- Section 12: Horizontal bar chart with lifecycle stage colors
- .bar-fill with transition: width 0.3s smooth animation
- Stage color variants: imported/cyan, indexed/blue, pdf-ready/purple
- fulltext-ready/green, deep-read/yellow, ai-ready/red
- All colors use var(--*) Obsidian CSS variables
2026-05-04 14:35:37 +08:00
Research Assistant
2bc1372e60 feat(27-01): add lifecycle stepper and health matrix CSS components
- Section 9: Lifecycle stepper with 6 vertical steps, border-radius circles
- Connecting lines via ::before pseudo-element between steps
- States: .completed (green), .current (pulsing), .pending (dimmed)
- Section 10: Health matrix 2x2 CSS grid with color-coded cells
- Status classes: .ok (green), .warn (yellow), .fail (red)
- Hover tooltips via [title]:hover::after with attr(title)
- All colors use var(--*) Obsidian CSS variables
2026-05-04 14:34:56 +08:00
Research Assistant
8f1286df35 feat(27-01): add loading skeleton shimmer and enhanced metric card CSS
- Section 7: Loading skeleton with @keyframes paperforge-shimmer (1.5s)
- Section 7: Empty state with muted italic styling via .paperforge-empty-state
- Section 2 enhanced: opacity 0.3s transition on metric-card and metric-value
- Added .paperforge-metric-progress and .paperforge-metric-progress-fill for optional progress bar
- All colors use var(--*) Obsidian CSS variables
2026-05-04 14:34:11 +08:00
Research Assistant
bc88aac6d5 docs(27): capture phase 27 context (component library) 2026-05-04 14:24:45 +08:00
Research Assistant
de019a4ca7 docs: create milestone v1.7 roadmap (4 phases, context-aware dashboard) 2026-05-04 14:18:44 +08:00
Research Assistant
ec28ea143f docs: define milestone v1.7 requirements (context-aware dashboard) 2026-05-04 14:12:01 +08:00
Research Assistant
27afbc401c chore: bump version to v1.4.15 2026-05-04 13:03:11 +08:00
Research Assistant
d1fb6e69ca fix: restore ROADMAP.md (was rewritten for v1.7, not deleted) 2026-05-04 13:01:59 +08:00
Research Assistant
ce6aaeed71 chore: delete archived REQUIREMENTS.md and ROADMAP.md (archived to milestones/) 2026-05-04 13:01:47 +08:00
Research Assistant
7646cb5b07 chore: add v1.6.0 to plugin versions.json 2026-05-04 13:01:30 +08:00
Research Assistant
a283806abf chore: bump version to v1.6.0 2026-05-04 13:01:13 +08:00
Research Assistant
9a4d38d00e chore: complete v1.6 AI-ready literature asset foundation milestone 2026-05-04 13:00:43 +08:00
Research Assistant
e113e49c6e docs(26-03): complete plugin Copy Context actions 2026-05-04 12:52:16 +08:00
Research Assistant
ecbb7766dd feat(26-03): add Copy Context Quick Action with key resolution
- Add paperforge-copy-context ACTIONS entry with needsKey flag
- Update _runAction to resolve zotero_key from active file frontmatter
- Add needsFilter support for collection context (--all default)
- Implement clipboard copy with JSON validation for context commands
- Add running guard to prevent simultaneous execution
- Add variable timeout (30s context, 60s collection, 600s other)
- Register command palette entries for both context actions
2026-05-04 12:51:07 +08:00
Research Assistant
e5a2102783 docs(26-02): complete context CLI command plan 2026-05-04 12:47:49 +08:00
Research Assistant
c753a96e39 test(26-01): add migration tests for flat-to-workspace, _build_entry workspace write, and idempotency
- test_migrate_flat_note_to_workspace: D-11/D-12 copy-not-move verification
- test_migrate_extracts_deep_reading: D-13 deep-reading.md extraction
- test_migrate_creates_ai_dir: ai/ directory creation
- test_migrate_idempotent_skips_existing: D-15 idempotency
- test_build_entry_writes_to_workspace_after_migration: workspace-aware _build_entry
- test_build_entry_flat_fallback_for_unmigrated_paper: backward compat fallback
- test_build_entry_new_paper_creates_workspace: new paper behavior
- test_run_index_refresh_calls_migrate: spy on run_index_refresh integration
- bonus: test_migrate_returns_zero_when_no_index
2026-05-04 12:46:31 +08:00
Research Assistant
09dab7e206 test(26-02): write 14 tests for context command modes and provenance output
- TestContextSingleKey: single key JSON object with _provenance and _ai_readiness
- TestContextSingleKeyNotFound: missing key returns 1 with error
- TestContextDomainFilter: --domain filters correctly (AIC-03)
- TestContextCollectionFilter: --collection prefix match (AIC-03)
- TestContextAll: --all returns all entries
- TestContextProvenanceTraceability: all 9 provenance path keys present (AIC-04)
- TestContextAiReadinessBlocking: blocking explanation for pdf_ready/fulltext_ready
- TestContextNoEntriesMatch: empty results and no-mode error
- TestContextIndexMissing: missing index guidance
2026-05-04 12:45:52 +08:00
Research Assistant
8e8677dd63 feat(26-01): add migrate_to_workspace() and update _build_entry() for workspace path writing
- Add migrate_to_workspace() function to sync.py that copies flat notes to workspace directories
- Extract ## 🔍 精读 section into deep-reading.md in workspace
- Create ai/ directory in each paper workspace
- Wire migration into run_index_refresh() before build_index()
- Update _build_entry() in asset_index.py to write notes to workspace path when workspace dir exists
- Preserve flat path fallback for backward compatibility when workspace dir does not exist
2026-05-04 12:44:25 +08:00
Research Assistant
ace77d538e feat(26-02): wire context command into CLI subparser, registry, and dispatch
- Add 'context' to _COMMAND_REGISTRY for dynamic module loading
- Add context subparser with key (nargs='?'), --domain, --collection, --all
- Dispatch in main() to paperforge.commands.context.run(args)
- D-06: always outputs JSON, no --json flag needed
2026-05-04 12:43:43 +08:00
Research Assistant
f933075cff feat(26-02): create context command module with single-key and filter modes
- run() reads canonical index, filters by key/domain/collection/all
- _format_context_entry wraps entries with _provenance and _ai_readiness blocks
- AIC-04: blocking explanation when lifecycle != 'ai_context_ready'
- AIC-02: single key outputs single JSON object with provenance
- AIC-03: --domain and --collection output JSON arrays
- D-01: canonical index entry IS the AI context -- no separate pack format
2026-05-04 12:43:14 +08:00
Research Assistant
0739d29c65 docs(26): add workspace migration scope (flat→folder, preserve deep reading) 2026-05-04 12:33:34 +08:00
Research Assistant
a863ebcb24 docs(26): capture phase 26 context (AI context packs) 2026-05-04 12:01:30 +08:00
Research Assistant
8032478f54 docs(25-03): complete Base views lifecycle columns + repair build_index plan 2026-05-04 11:36:44 +08:00
Research Assistant
36dccf13a3 fix(25-03): use double-quote YAML wrapping for lifecycle filter values
- Filters now contain single-quoted lifecycle values (e.g. lifecycle = 'fulltext_ready')
  which broke single-quote YAML wrapping; switched to double-quote wrapper
- Updated _render_views_section(), merge_base_views(), _build_base_yaml()
- Updated filter preservation test to use lifecycle-based filter strings
2026-05-04 11:35:17 +08:00
Research Assistant
1ab6628796 docs(25-01): update ROADMAP progress to 1/3 2026-05-04 11:28:58 +08:00
Research Assistant
e49296f1bb docs(25-01): complete status --json source migration + doctor Index Health plan 2026-05-04 11:28:27 +08:00
Research Assistant
a8eece83e8 feat(25-01): refactor run_status to read canonical index + add doctor Index Health
- run_status() reads canonical index via summarize_index() for lifecycle,
  health, and maturity aggregates; falls back to filesystem when index missing
- JSON output includes lifecycle_level_counts, health_aggregate,
  maturity_distribution (or None when falling back)
- Text output shows lifecycle and health lines when index is present
- run_doctor() shows Index Health section with PDF/OCR/Note/Asset Health
  counts and status per dimension
- Brownfield detection: legacy schema, old Base templates, partial OCR assets
- Fixed status_tag mapping to support 'info' status (existing bug)
- 6 new tests covering index-backed JSON output, fallback, text output,
  Index Health with/without index, and mixed health counts

Phase 25-01, Tasks 2+3
2026-05-04 11:26:39 +08:00
Research Assistant
a7a4abdfde docs(25-02): complete plugin dashboard direct JSON read + doctor/repair Quick Actions 2026-05-04 11:25:31 +08:00
Research Assistant
00cd475f74 feat(25-03): wire repair to call build_index() after fixing source artifacts
- Add build_index() call at end of run_repair() when fix=True or fix_paths=True
- Add 'rebuilt' key to result dict initialization
- Add user-facing messages about repair completion and recovery path (MIG-04)
- Lazy import inside conditional block to avoid circular dependency
- Add tests: build_index called after fix, not called during dry-run,
  rebuilt in result, error fallback on build_index failure
2026-05-04 11:25:12 +08:00
Research Assistant
d143c2ed1b feat(25-02): add doctor and repair Quick Action buttons
- Add 'paperforge-doctor' action: runs 'python -m paperforge doctor'
- Add 'paperforge-repair' action: runs 'python -m paperforge repair'
- ACTIONS array now has 4 entries: sync, ocr, doctor, repair
- Existing _runAction() handles both new commands unchanged (thin CLI shell)
2026-05-04 11:23:56 +08:00
Research Assistant
bd6226669d feat(25-03): update Base views with lifecycle-based columns, filters, and sort order
- Replace has_pdf/do_ocr/analyze/ocr_status columns with lifecycle/maturity_level/next_step
- Update filters to use lifecycle states instead of raw status combinations
- Add sort by lifecycle ascending to all views
- Update PROPERTIES_YAML and _build_base_yaml properties
- Add sort YAML rendering in _render_views_section and merge_base_views
- Update existing filter tests to match lifecycle semantics
- Add tests: lifecycle columns, removed old columns, lifecycle filters, sort, properties
2026-05-04 11:23:38 +08:00
Research Assistant
86d142e7fd feat(25-02): refactor _fetchStats to read formal-library.json directly
- Replace Python CLI spawn with fs.readFileSync for primary path
- Single-pass aggregation of lifecycle, health, and OCR counts per D-06
- Fallback to CLI spawn when index file is missing (D-07)
- Add fs and path as top-level requires
- Access system_dir via app.plugins.plugins['paperforge'].settings
2026-05-04 11:23:29 +08:00
Research Assistant
a431632b3c feat(25-01): add summarize_index() helper to asset_index.py
- New function summarize_index() reads canonical index and returns lifecycle,
  health, and maturity aggregates
- Returns None for missing or legacy bare-list index
- 4 new tests: aggregates, missing, legacy format, empty items

Phase 25-01, Task 1
2026-05-04 11:22:46 +08:00
Research Assistant
b8c5cf881a docs(25): create phase 25 surface convergence plans
3 plans in 1 wave:
- 25-01: status --json source migration + doctor Index Health + brownfield detection
- 25-02: Plugin dashboard direct JSON read + doctor/repair Quick Actions
- 25-03: Base views lifecycle columns + repair source-first rebuild pattern
2026-05-04 11:20:00 +08:00
Research Assistant
043df53bc7 test(24-02): add integration tests for derived state fields in index entries
- Add TestDerivedStateFields class with 6 test methods
- Verify lifecycle/health/maturity/next_step present after full build
- Verify same fields present after incremental refresh
- Verify lifecycle is a valid state string
- Verify health dict has four dimension keys
- Verify maturity structure (level, level_name, checks, blocking)
- Verify next_step is a valid action string
2026-05-04 10:43:43 +08:00
Research Assistant
8fd963f10b feat(24-02): add lifecycle, health, maturity, next_step to canonical index entries
- Import compute_lifecycle, compute_health, compute_maturity, compute_next_step from asset_state
- Call all four functions after entry dict construction in _build_entry()
- New fields flow automatically through build_index() and refresh_index_entry()
2026-05-04 10:42:06 +08:00
Research Assistant
36cb9aa9c0 docs(24-01): complete asset state derivation plan
- SUMMARY.md with TDD cycle documentation and 3 auto-fixes
- STATE.md: advanced to next plan, 78% overall progress
- ROADMAP.md: Phase 24 status updated (1/2 plans complete)
- REQUIREMENTS.md: STATE-01..04 and AIC-01 marked complete
2026-05-04 10:38:49 +08:00
Research Assistant
1528550e4a refactor(24-01): polish asset_state docstrings and edge cases
- Fix note_health to use ternary expression (ruff SIM108)
- All docstrings describe inputs, outputs, and derivation rules
- Module-level docstring lists all four exports
- All 26 tests pass, ruff: All checks passed
2026-05-04 10:36:22 +08:00
Research Assistant
32281262a5 feat(24-01): implement asset_state derivation functions
- compute_lifecycle: six progressive states (indexed → pdf_ready → fulltext_ready → deep_read_done → ai_context_ready)
- compute_health: four dimensions (pdf/ocr/note/asset) with concrete fix instructions
- compute_maturity: level 1-6 with per-check pass/fail and blocking indicator
- compute_next_step: priority-ordered recommendation (sync/ocr//pf-deep/ready)
- All 26 tests pass, pure functions with no filesystem or config imports
2026-05-04 10:35:27 +08:00
Research Assistant
7daffab4a4 test(24-01): add failing tests for asset_state derivation functions
- Class TestComputeLifecycle: 8 tests covering indexed, pdf_ready, fulltext_ready, deep_read_done, ai_context_ready states
- Class TestComputeHealth: 4 tests covering all four health dimensions
- Class TestComputeMaturity: 6 tests covering levels 1-6 with blocking indicators
- Class TestComputeNextStep: 8 tests covering sync, ocr, /pf-deep, ready recommendations
- All 26 tests fail with ModuleNotFoundError (module not yet created)
2026-05-04 10:32:19 +08:00
Research Assistant
14c11ee2ed docs(24): create phase plan — derived lifecycle, health & maturity (2 plans, 6 tasks) 2026-05-04 10:25:05 +08:00
Research Assistant
242bbf145c docs(24): capture phase 24 context (lifecycle health maturity) 2026-05-04 10:10:26 +08:00
Research Assistant
e9e1131103 fix(23): use Beijing time (UTC+8) for index timestamp, fix test stub signature 2026-05-04 01:08:13 +08:00
Research Assistant
15b4cfbac7 docs(23-03): complete incremental refresh wiring plan
- 4 tasks, 5 files modified/created
- OCR, deep-reading, repair now use incremental index refresh
- sync.py documented with full-rebuild convention
- 9 integration tests added
- Phase 23 complete (3/3 plans)
2026-05-04 00:57:16 +08:00
Research Assistant
c8561fd99a feat(23-03): add integration tests for incremental refresh across workers
- Add test_asset_index_integration.py with 9 tests:
  - refresh_index_entry preserves unrelated entries
  - refresh_index_entry appends new keys
  - refresh_index_entry falls back to build_index on legacy format
  - refresh_index_entry skips unknown keys gracefully
  - Structural checks for OCR, deep-reading, repair call sites
  - Workspace path fields present and consistent
- Fix indentation bug in repair.py (Rule 1 auto-fix from Task 3)
2026-05-04 00:55:17 +08:00
Research Assistant
a190c942e7 feat(23-03): add incremental refresh to repair operations and document sync convention
- Import refresh_index_entry in repair.py
- Call refresh_index_entry after each successful path fix in repair_pdf_paths
- Call refresh_index_entry after each divergence fix in run_repair
- Add docstring to run_index_refresh in sync.py explaining full-rebuild default
  convention vs incremental refresh by key
2026-05-04 00:51:56 +08:00
Research Assistant
3ec67535a0 feat(23-03): add incremental index refresh to deep-reading status sync
- Import refresh_index_entry from asset_index module
- After status sync report, refresh canonical index for every paper
- Refresh even when synced==0 (formal note content may have changed)
- Failure to refresh logs warning, does not abort the worker
2026-05-04 00:50:41 +08:00
Research Assistant
3557476c4f feat(23-03): switch OCR post-processing to incremental index refresh
- Add refresh_index_entry import from asset_index module
- Replace full rebuild (_sync.run_index_refresh) with incremental refresh per completed OCR key
- Capture done keys before queue filter to preserve them for incremental refresh
- Add ImportError fallback to full rebuild for pre-migration safety
- When no OCR completed, still run full rebuild for sync changes
2026-05-04 00:49:59 +08:00
Research Assistant
493852c8aa docs(23-02): add self-check PASSED to SUMMARY 2026-05-04 00:48:01 +08:00
Research Assistant
566fc0c253 docs(23-02): complete legacy migration, incremental refresh, workspace paths plan
- SUMMARY.md with 3 task commits documented
- STATE.md advanced to Plan 3 of 3
- ROADMAP.md updated for Phase 23 progress (2/3 plans complete)
- REQUIREMENTS.md: ASSET-03 marked complete
2026-05-04 00:47:31 +08:00
Research Assistant
2886afa861 feat(23-02): add workspace path fields, frontmatter mirroring, and --rebuild-index CLI flag
- Add paper_root, main_note_path, fulltext_path, deep_reading_path, ai_path
  to _build_entry() result dict (Phase 22 paper workspace layout, D-12)
- Mirror workspace path fields in formal note frontmatter for Base views (D-14)
- Add --rebuild-index flag to cli.py sync command parser
- Thread rebuild_index parameter through commands/sync.py -> run_index_refresh()
- Existing system paths (ocr_path, meta_path, note_path) preserved (D-13)
- All 14 existing tests pass
2026-05-04 00:46:34 +08:00
Research Assistant
2fd37261db feat(23-02): implement incremental refresh (refresh_index_entry) and schema_version check
- Extract _build_entry() from build_index() loop body as shared helper
- Add refresh_index_entry(vault, key) for single-entry incremental update
- Add schema_version mismatch detection in build_index()
- Lazy imports inside _build_entry() avoid circular deps with sync.py
- Legacy format detected in refresh falls back to full rebuild
- All 14 existing tests pass
2026-05-04 00:44:23 +08:00
Research Assistant
6da41161b8 feat(23-02): add legacy format detection, backup, and auto-migration to build_index
- Add read_index(vault) to read existing index file safely
- Add is_legacy_format(data) to distinguish bare-list from envelope
- Add migrate_legacy_index(vault) to copy legacy index to .bak before rebuild
- Modify build_index() to call migrate_legacy_index at start
- Corrupt/missing files handled gracefully (treated as fresh build)
2026-05-04 00:42:16 +08:00
Research Assistant
7eecf08c96 docs(23-01): complete canonical-asset-index-safe-rebuilds plan 2026-05-04 00:38:09 +08:00
Research Assistant
ccd79038c2 test(23-01): add tests for asset_index.py core functionality
- TestGetIndexPath: path resolution to indexes/formal-library.json
- TestBuildEnvelope: empty/with-items/count-matching/ISO timestamp
- TestAtomicWriteIndex: file creation, content correctness, atomicity
  on interrupt, parent dir creation, overwrite, lock timeout via threading
- TestBuildIndexEmpty: empty exports dir and absent exports dir return 0
  and write empty envelope
- 14 tests passing
2026-05-04 00:36:15 +08:00
Research Assistant
87437cfd5e feat(23-01): create asset_index.py module with envelope, atomic writes, and build_index extraction
- New asset_index.py module with build_index(), get_index_path(), atomic_write_index()
- build_envelope() wraps items in versioned envelope (schema_version, generated_at, paper_count, items)
- atomic_write_index() uses tempfile.NamedTemporaryFile + os.replace for Windows-safe atomic writes
- Cross-process locking via filelock.FileLock with 10-second timeout
- build_index() extracted from sync.py run_index_refresh loop (lines 1686-1746)
- sync.py run_index_refresh() delegates to asset_index.build_index()
- Orphaned-record cleanup stays in sync.py
2026-05-04 00:34:54 +08:00
Research Assistant
a2c6c8bf42 chore(23-01): add filelock>=3.13.0 dependency
- Added filelock>=3.13.0 to pyproject.toml dependencies
- Required for cross-process locking during index writes
2026-05-04 00:29:08 +08:00
Research Assistant
e33ebfa77d docs(23): capture phase 23 context (canonical asset index) 2026-05-04 00:19:27 +08:00
Research Assistant
c6bf50771f docs(22-03): complete setup-doctor-migration-and-config-source-tracing plan 2026-05-03 23:13:21 +08:00
Research Assistant
f5db36326d feat(22-03): add config source tracing to load_vault_config for CONF-03 inspection 2026-05-03 23:10:50 +08:00
Research Assistant
6f91f73630 feat(22-03): extend doctor with Config Migration detection and schema_version display 2026-05-03 23:08:56 +08:00
Research Assistant
d0b050cf70 feat(22-03): setup wizard writes clean vault_config-only paperforge.json with schema_version 2026-05-03 23:07:38 +08:00
Research Assistant
1065ea77b0 docs(22-02): complete plugin-paperforge-json-config-truth plan
- SUMMARY: Refactored plugin to read path config from paperforge.json (vault_config), eliminating second runtime truth
- DEFAULT_SETTINGS: Removed 5 path keys, kept 7 non-path keys
- Added readPaperforgeJson(), savePaperforgeJson(), refactored loadSettings/saveSettings
- PaperForgeSettingTab now sources path display from paperforge.json (_pfConfig cache)
- 1 deviation: added paddleocr_api_key and zotero_data_dir to DEFAULT_SETTINGS (data-loss prevention)
- Requirements completed: CONF-01, CONF-04
2026-05-03 22:59:56 +08:00
Research Assistant
36de493367 feat(22-02): add savePaperforgeJson() and clean stale path fields from plugin data.json on load
- Added savePaperforgeJson() method writing path config to paperforge.json vault_config block
- savePaperforgeJson() removes stale top-level path keys, sets schema_version='2' if absent
- After write, refreshes in-memory plugin.settings path fields from paperforge.json
- Added saveSettings() call in onload() to clean stale path fields from plugin data.json on first load
- saveSettings() already filters by DEFAULT_SETTINGS keys (from Task 1), automatically excluding path fields
2026-05-03 22:56:13 +08:00
Research Assistant
cda3cff9f7 feat(22-02): refactor SettingsTab display to source path config from paperforge.json
- Added _pfConfig cache and _refreshPfConfig() to PaperForgeSettingTab constructor
- display() now calls _refreshPfConfig() at start for fresh path config
- Config Summary section reads path values from _pfConfig (paperforge.json source)
- Prep export path hint now reads from _pfConfig.system_dir
- Non-path fields (paddleocr_api_key, zotero_data_dir) still read from plugin.settings
2026-05-03 22:54:42 +08:00
Research Assistant
00ae8e83f1 feat(22-02): add readPaperforgeJson(), clean DEFAULT_SETTINGS, refactor loadSettings/saveSettings
- Removed path directory keys (system_dir, resources_dir, literature_dir, control_dir, base_dir) from DEFAULT_SETTINGS
- Kept non-path keys: vault_path, setup_complete, auto_update, agent_platform, language, paddleocr_api_key, zotero_data_dir
- Added readPaperforgeJson() method reading from paperforge.json vault_config block with Python DEFAULT_CONFIG fallback
- Refactored loadSettings() to overwrite path fields from readPaperforgeJson()
- Refactored saveSettings() to only persist DEFAULT_SETTINGS keys (excludes path fields)
- Updated prep export path hint default from 'System' to '99_System'
2026-05-03 22:53:18 +08:00
Research Assistant
4c393ede9a docs(22-01): complete Python config migration plan
Metadata: SUMMARY.md, STATE.md, ROADMAP.md, REQUIREMENTS.md updated
2026-05-03 22:43:50 +08:00
Research Assistant
37ce6ecd70 feat(22-01): wire config migration into sync command
- Import migrate_paperforge_json from paperforge.config
- Call migrate_paperforge_json after vault resolution, before sync ops
- Log migration info; print verbose message when --verbose is set
2026-05-03 22:42:05 +08:00
Research Assistant
e2d3f5a927 feat(22-01): implement config migration engine
- Add import shutil to config.py
- Add CONFIG_PATH_KEYS tuple for legacy top-level path keys
- Add migrate_paperforge_json() function with gap-fill logic
- Backs up original as paperforge.json.bak before writing
- Idempotent: no-op for already-migrated files
- Non-path top-level keys (version, agent_platform) survive migration
2026-05-03 22:41:13 +08:00
Research Assistant
8067baf15f test(22-01): add failing tests for config migration engine
- Legacy top-level keys migrate to vault_config block
- Idempotent: already-migrated files return False
- No paperforge.json returns False safely
- Non-path keys survive in output root
- vault_config block is created when missing
2026-05-03 22:39:45 +08:00
Research Assistant
e0850708ca feat(22-01): implement schema_version in config layer
- Add schema_version: '2' as first key in DEFAULT_CONFIG
- Add get_paperforge_schema_version() public function
- Exclude schema_version from load_vault_config() output
- CONFIG_KEYS auto-derives from DEFAULT_CONFIG via set()
2026-05-03 22:39:09 +08:00
Research Assistant
4c76fb1e4a test(22-01): add failing tests for schema_version feature
- DEFAULT_CONFIG must contain schema_version: '2'
- CONFIG_KEYS must include schema_version
- get_paperforge_schema_version() defaults to 1 when key absent
- get_paperforge_schema_version() reads explicit value
- load_vault_config() excludes schema_version from output
2026-05-03 22:37:56 +08:00
Research Assistant
09c7f17738 docs(22): create phase 22 plans (config schema, migration, plugin truth, setup cleanup)
- 22-01: Python config layer (schema_version, migration engine, sync hook)
- 22-02: Plugin config truth (reads paperforge.json, no DEFAULT_SETTINGS path fields)
- 22-03: Setup wizard cleanup + doctor migration detection + config source tracing
- Covers CONF-01..CONF-04 across 3 plans in 2 waves
2026-05-03 22:34:35 +08:00
Research Assistant
d4008c7bc7 docs(22): capture phase 22 context (configuration truth) 2026-05-03 22:22:58 +08:00
Research Assistant
c5889e4a5b docs: create milestone v1.6 roadmap (5 phases) 2026-05-03 13:52:25 +08:00
Research Assistant
56c25c6b5e docs: define milestone v1.6 requirements 2026-05-03 13:48:49 +08:00
Research Assistant
2501278166 docs: complete project research 2026-05-03 13:46:11 +08:00
Research Assistant
8f72a5ba68 docs: start milestone v1.6 AI-ready literature asset foundation 2026-05-03 13:37:31 +08:00
Lin Zhaoxuan
b0b6424edc
更新 README.md 2026-05-02 17:17:16 +08:00
Lin Zhaoxuan
a5e37dc0f1
更新 README.md 2026-05-02 17:16:06 +08:00
Research Assistant
2e252525e6 chore: bump version to v1.4.14 2026-05-02 15:20:25 +08:00
Research Assistant
f2974fee0e feat: refine plugin onboarding copy and dashboard branding 2026-05-02 15:18:51 +08:00
Research Assistant
548417a8c5 docs: update dashboard screenshot 2026-05-02 14:56:14 +08:00
Research Assistant
04adc36b9b docs: redesign README with banner and dashboard preview 2026-05-02 14:52:59 +08:00
Research Assistant
d888173a26 fix: bump.py creates tags without v prefix (Obsidian compatibility) 2026-05-01 12:17:14 +08:00
Research Assistant
3bc838a59d fix: sync description across manifests; fix authorUrl to personal URL 2026-05-01 12:16:15 +08:00
Research Assistant
b5b6c832f0 chore: add manifest.json at repo root; remove 'Obsidian' from description 2026-05-01 12:11:48 +08:00
Research Assistant
099f0d1029 chore: remove legacy i18n.js (i18n inlined in main.js) 2026-05-01 11:47:12 +08:00
Research Assistant
8bb96eb486 docs: sync license and acknowledgments in Chinese README; fix license badge 2026-05-01 11:39:14 +08:00
Research Assistant
f2c1130b2a docs: add CC BY-NC-SA 4.0 license and acknowledgments 2026-05-01 11:37:50 +08:00
Research Assistant
984460c97f chore: bump version to v1.4.13 2026-05-01 11:14:59 +08:00
Research Assistant
c6ef0e6513 fix: continuous OCR batch processing + real-time dashboard progress + fix loading flicker 2026-04-30 16:05:02 +08:00
Research Assistant
49b6c5772b feat: replace exec with spawn for Dashboard actions (real-time OCR/sync progress) 2026-04-30 14:33:05 +08:00
Research Assistant
47d7ec227e chore: bump version to v1.4.12 2026-04-30 14:12:45 +08:00
Research Assistant
2b3bf78c63 fix: add header_title key, fix lang detection, complete config summary i18n 2026-04-30 14:11:03 +08:00
Research Assistant
03dd7ecc39 fix: inline i18n into main.js (remove require/i18n.js deps) 2026-04-30 14:05:04 +08:00
Research Assistant
ece6c9b2ba feat: complete i18n refactor + automated release script
- i18n.js: zh/en language pack with auto-detect from Obsidian config
- main.js: all UI strings use t() calls (settings tab, wizard, pre-check)
- scripts/bump.py: --release flag: bump + commit + tag + push + gh release
- AGENTS.md: developer guide section (bump, release, i18n, pre-commit)
2026-04-30 13:55:54 +08:00
Research Assistant
4190065008 docs: add developer guide (version bump, release, i18n, pre-commit) 2026-04-30 13:33:48 +08:00
Research Assistant
b7a313fdd6 chore: add automated version bump script (bump.py) 2026-04-30 13:29:26 +08:00
Research Assistant
8f7d7302a3 feat: add i18n framework (zh/en auto-detect) + author fix + versions.json update 2026-04-30 13:28:24 +08:00
Research Assistant
c33a01e2d0 chore: update versions.json to v1.4.11; sync script covers both json files 2026-04-30 12:59:45 +08:00
Research Assistant
5164ac8054 chore: add version sync script (__init__.py -> manifest.json) 2026-04-30 12:56:28 +08:00
Research Assistant
55af355361 chore: bump plugin manifest to v1.4.11 2026-04-30 12:54:22 +08:00
Research Assistant
aa3d4a7793 docs: rewrite Chinese README for plugin-first experience 2026-04-30 11:20:41 +08:00
Research Assistant
620ddeb0b7 docs: rewrite README for Obsidian plugin-first experience 2026-04-30 11:18:52 +08:00
Research Assistant
9412c154dd feat: v1.4.11 — Obsidian plugin UX overhaul + headless_setup parity
- Plugin: multi-step install wizard modal (5 steps) with editable directory/key inputs
- Plugin: settings tab becomes operation guide; all config moved to wizard
- Plugin: Python/Zotero/BBT pre-check before wizard opens
- Plugin: agent platform selector (OpenCode/Claude/Cursor/Copilot etc.)
- Plugin: responsive dashboard (auto-fit grids, clamp typography)
- Plugin: command output styled in-panel (running/ok/error)
- Plugin: BBT export guidance in settings tab
- Plugin: rename defaults (Resources, Notes, Index_Cards, System, Base)
- Plugin: vault_path auto-detect from Obsidian
- Plugin: auto-update paperforge on plugin load
- CLI: headless_setup now creates Zotero junction (mklink /J)
- CLI: headless_setup deploys skill directory for flat_command agents
- sync: wikilink through junction (no .resolve() — keeps vault-relative paths)
- sync: route absolute paths through Zotero junction for vault-relative wikilinks
- config: remove library-records subdirectory (records now directly under control_dir)
- base_views: fix duplicate views on merge (skip legacy unmarked views)
- base_views: auto-update folder filter when path config changes
- Phases 20-22 planned and documented
- Bump to v1.4.11
2026-04-30 11:14:07 +08:00
Research Assistant
3e06ce354a docs(21-01): final ROADMAP and STATE update for v1.5 milestone delivery
- Mark Phase 21 complete (2/2 plans)
- Mark v1.5 milestone shipped (Phases 20-21, 2026-04-29)
- Update STATE.md to COMPLETE status
2026-04-29 22:41:10 +08:00
Research Assistant
fb23cd01c3 docs(21-01): complete One-Click Install & Polished UX plans
- 21-01: Install button UI, _validate(), CSS status styles
- 21-02: _runSetup() spawn, Chinese error mapping, progress helpers
- Mark INST-01/02/03/04 complete
- Update STATE.md, ROADMAP.md for Phase 21 completion
2026-04-29 22:40:21 +08:00
Research Assistant
58038988ef feat(21-01): add subprocess orchestration and Chinese notice helpers
- _runSetup(): validates fields, spawns paperforge setup --headless, disables/enables button
- Uses spawn (not exec) for stdout streaming, --headless (not --non-interactive)
- Explicit directory args override headless_setup defaults
- _showNotice(): renders success/error/progress via Obsidian Notice API
- _formatSetupError(): maps 5+ error patterns to Chinese, raw errors logged to console
- _processSetupOutput(): parses [*]/[OK]/[FAIL] step markers from stdout
- _setStatus(): updates status area with color-coded CSS class
- Button disable/enable in try/finally prevents double-click
- INST-04: sidebar and commands unchanged
2026-04-29 22:38:22 +08:00
Research Assistant
dc6be1c5ed feat(21-01): add install status CSS styles (SECTION 5)
- .paperforge-install-status base style with margin/padding/border-radius
- .paperforge-install-success (green) with color-mix tinted background
- .paperforge-install-error (red) with color-mix tinted background
- .paperforge-install-progress (blue) with color-mix tinted background
- Uses Obsidian CSS variables for theme compatibility
2026-04-29 22:36:24 +08:00
Research Assistant
0d60dd6b1d feat(21-01): add _validate() field validation method
- Check 7 required fields for non-empty values
- All error messages in Chinese per INST-03
- zotero_data_dir excluded (optional field, auto-detected)
- Returns empty array when valid, error strings array when invalid
2026-04-29 22:36:05 +08:00
Research Assistant
2f1feec24d feat(21-01): add install button section and status area to settings tab
- Append '\u5b89\u88c5\u914d\u7f6e' section with status div + CTA button
- Create _statusArea with initial status message
- Button onClick wired to _runSetup (forward declaration for Plan 02)
- No existing code modified (sidebar, actions, other sections preserved)
2026-04-29 22:35:46 +08:00
Research Assistant
dfffc05fd2 feat(20-20): add settings data model with DEFAULT_SETTINGS and PaperForgeSettingTab UI
- DEFAULT_SETTINGS: vault_path, system_dir, resources_dir, literature_dir, control_dir, agent_config_dir, paddleocr_api_key, zotero_data_dir
- Plugin.loadSettings() merges DEFAULT_SETTINGS with saved data via Object.assign
- Plugin.saveSettings() persists via Obsidian Plugin.saveData() API
- PaperForgeSettingTab with 3 sections: 基础路径 (6 fields), API 密钥 (1 password), Zotero 链接 (1 field)
- Debounced 500ms save on field change via setTimeout/clearTimeout pattern
- 8 settings text inputs: 7 regular + 1 password field for paddleocr_api_key
- Settings survive tab switch (in-memory state) and Obsidian restart (data.json persistence)
2026-04-29 22:20:07 +08:00
Research Assistant
08feda3953 fix: include styles.css in package data; prevent Unicode crash on pip output 2026-04-29 01:06:59 +08:00
Research Assistant
0741d65d6d fix: sync Obsidian plugin even when update is already current 2026-04-29 00:57:30 +08:00
Research Assistant
bac8414456 fix: read remote version from GitHub API content to avoid raw CDN cache 2026-04-29 00:29:45 +08:00
Research Assistant
a4c8d21284 chore: bump to v1.4.8 and unify update version checks on __init__.py 2026-04-29 00:26:16 +08:00
Research Assistant
c12128ede9 fix: update pip installs from GitHub source instead of package index 2026-04-29 00:16:13 +08:00
Research Assistant
cad6a3372d fix: move install_obsidian_plugin to _utils.py, reload after update to always use latest code 2026-04-29 00:09:52 +08:00
Research Assistant
fc50ecda1e fix: correct UPDATEABLE_PATHS repo paths; plugin install uses vault-first source; exclude table images from figure-map matching 2026-04-28 23:58:02 +08:00
Research Assistant
001de61cdb chore: bump to v1.4.5 2026-04-28 23:43:47 +08:00
Research Assistant
8e36c1d466 refactor: extract pipeline_paths into _utils.py — remove 7 copies, 3 of which were dead code 2026-04-28 23:42:00 +08:00
Research Assistant
9f5c749376 refactor: extract load_domain_config into single _domain.py module — remove 7 copies, full rebuild on every call 2026-04-28 23:31:31 +08:00
Research Assistant
18a8de68d5 feat: overhaul Obsidian plugin UI — dashboard layout, segmented OCR bar, action cards 2026-04-28 23:14:52 +08:00
Research Assistant
94fedd30fe refactor: __init__.py as single version source; pyproject.toml reads dynamically; paperforge.json drops version field 2026-04-28 22:41:48 +08:00
Research Assistant
3fd479adf9 chore: bump to v1.4.4 to unify all fixes under a single version 2026-04-28 22:34:41 +08:00
Research Assistant
86b9fd85f4 fix: reload paperforge module before installing plugin to get updated path 2026-04-28 22:31:13 +08:00
Research Assistant
74cde0594d fix: surface remote version check errors instead of silently swallowing 2026-04-28 22:23:28 +08:00
Research Assistant
3f3d4ba6fa feat: paperforge update now auto-installs Obsidian plugin 2026-04-28 22:18:42 +08:00
Research Assistant
d7bc70e847 fix: sync __version__ to 1.4.3, _remote_version() reads from __init__.py 2026-04-28 22:13:23 +08:00
Research Assistant
30cec519a9 chore: bump to v1.4.3, update READMEs with multi-agent and plugin info 2026-04-28 19:43:58 +08:00
Research Assistant
ae2f78d424 feat: paperforge status --json, plugin panel with OCR progress bar 2026-04-28 19:21:52 +08:00
Research Assistant
864e2dcd9a feat: Obsidian plugin status panel — metric cards, progress bars, quick actions 2026-04-28 19:11:58 +08:00
Research Assistant
f243a6977a fix: restructure skills — separate pf-deep/pf-paper, add prefix substitution, create config_file on deploy 2026-04-28 18:33:11 +08:00
Research Assistant
4966c0c369 merge: feature/multi-agent-platform into master 2026-04-28 18:08:27 +08:00
Research Assistant
f2f884877c fix: apply missing deploy helper functions, SKILL.md source files, and format dispatch 2026-04-28 17:15:37 +08:00
Research Assistant
fc72612982 fix: ensure parent dirs exist before copying skill files 2026-04-28 16:27:45 +08:00
Research Assistant
72bb9ce34d test: add integration smoke tests for multi-agent deploy 2026-04-28 16:27:31 +08:00
Research Assistant
df2057b42b test: add AGENT_CONFIGS format/prefix field tests, update expected agents 2026-04-28 16:13:58 +08:00
Research Assistant
34427e2242 fix: remove hardcoded literature-qa subdirs from Phase 2 directory creation 2026-04-28 16:11:59 +08:00
Research Assistant
730faf2843 feat: add SKILL.md source files for skill_directory agents 2026-04-28 16:11:02 +08:00
Research Assistant
42b291fada refactor: replace OpenCode-only deploy with format-based dispatch 2026-04-28 16:09:42 +08:00
Research Assistant
0eebb86725 feat: add format-specific deploy helper functions 2026-04-28 16:06:02 +08:00
Research Assistant
eacac4f3ca refactor: extend AGENT_CONFIGS with format and prefix fields, add codex 2026-04-28 16:03:11 +08:00
Research Assistant
3a762ae1e6 gitignore: add .worktrees/ 2026-04-28 16:02:04 +08:00
Research Assistant
792f039e9f docs(plan): multi-agent platform implementation plan 2026-04-28 16:00:58 +08:00
Research Assistant
bd301fc4d5 docs(spec): add multi-agent platform design spec 2026-04-28 15:51:03 +08:00
Research Assistant
7dcf0b8f1f docs: split AI setup guide into EN and ZH versions 2026-04-28 15:01:31 +08:00
Research Assistant
4ce0f75b3e docs: bilingual AI setup guide — detect language, use matching prompts 2026-04-28 14:50:18 +08:00
Research Assistant
a26e943499 docs: bilingual AI install prompts, add cd-to-vault step 2026-04-28 14:44:44 +08:00
Research Assistant
8efcad4e5d chore: bump version to 1.4.2 2026-04-28 14:33:35 +08:00
Research Assistant
2d28ae841d docs: Zotero data dir — auto-detect first, always let user override 2026-04-28 14:33:35 +08:00
Research Assistant
71efe2b5f4 docs: rewrite AI setup guide — ask ALL params, explain dirs, promote BBT JSON export 2026-04-28 14:33:35 +08:00
Research Assistant
2ca557bb9e feat: headless setup mode, Obsidian plugin, AI agent install guide (v1.4.2) 2026-04-28 14:33:35 +08:00
Lin Zhaoxuan
596faec4ec
Update README with PaperForge setup command
Add installation instructions for PaperForge.
2026-04-28 13:36:12 +08:00
Lin Zhaoxuan
a0d6ec6e49
Update README with PaperForge setup instructions
Added installation instructions for PaperForge.
2026-04-28 13:35:40 +08:00
1631 changed files with 9877 additions and 504432 deletions

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import paperforge

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---
name: ask-matt
description: Ask which skill or flow fits your situation. A router over the skills in this repo.
disable-model-invocation: true
---
# Ask Matt
You don't remember every skill, so ask.
A **flow** is a path through the skills. Most paths run along one **main flow**, and two **on-ramps** merge onto it. Everything else is standalone, or a vocabulary layer that runs underneath.
## The main flow: idea → ship
The route most work travels. You have an idea and want it built.
1. **`/grill-with-docs`** — sharpen the idea by interview. Start here when you **have a codebase**: it's stateful, retaining what it learns in `CONTEXT.md` and ADRs. (No codebase? Use `/grill-me` — see Standalone. Both run the same `/grilling` primitive; `grill-with-docs` is the one that leaves a paper trail.)
2. **Branch — can you settle every question in conversation?** If a question needs a runnable answer (state, business logic, a UI you have to see), detour through a prototype, bridged by **`/handoff`** in both directions (see Crossing sessions):
- **`/handoff`** out, then open a fresh session against that file,
- **`/prototype`** to answer the question with throwaway code,
- **`/handoff`** back what you learned, and reference it from the original idea thread.
3. **Branch — is this a multi-session build?**
- **Yes****`/to-spec`** (turn the thread into a spec), then **`/to-tickets`** to split it into tracer-bullet tickets, each declaring its **blocking edges**. On a local tracker that's an ordered `tickets.md` you work by hand; on a real tracker the edges become native blocking links, so any ticket whose blockers are done can be grabbed — kick off **`/implement`** per ticket, **clearing context between each one**.
- **No****`/implement`** right here, in the same context window.
Either way, **`/implement`** builds each issue by driving **`/tdd`** internally — one red-green slice at a time — then closes out by running **`/code-review`**, a two-axis review (Standards + Spec) of the diff, before committing. Reach for **`/tdd`** on its own when you just want to build a concrete behaviour test-first without a full spec, and **`/code-review`** on its own whenever you want to review a branch or PR against a fixed point.
### Context hygiene
Keep steps 13 in **one unbroken context window** — don't compact or clear until after `/to-tickets` — so the grilling, spec, and tickets all build on the same thinking. Each `/implement` then starts fresh, working from the ticket.
The limit on this is the **[smart zone](https://www.aihero.dev/ai-coding-dictionary/smart-zone)**: the window (~120k tokens on state-of-the-art models) within which the model still reasons sharply. If a session approaches it before `/to-tickets`, don't push on degraded — `/handoff` and continue in a fresh thread.
## On-ramps
A starting situation that generates work, then merges onto the main flow.
- **Bugs and requests piling up****`/triage`**. It moves issues through triage roles and produces agent-ready issues, which **`/implement`** later picks up.
Triage is only for issues **you didn't create** — bug reports, incoming feature requests, anything that arrives raw. Tickets that `/to-tickets` produced are already agent-ready, so **don't triage them**.
- **Something's broken****`/diagnosing-bugs`**. For the hard ones: the bug that resists a first glance, the intermittent flake, the regression that crept in between two known-good states. It refuses to theorise until it has a **tight feedback loop** — one command that already goes red on *this* bug — then fixes with a regression test. Its post-mortem hands off to **`/improve-codebase-architecture`** when the real finding is that there's no good seam to lock the bug down.
- **A huge, foggy effort — a greenfield project or a huge feature build, too big for one session****`/wayfinder`**. When the way from here to the destination isn't visible yet, it charts a **shared map** of investigation tickets on the issue tracker and resolves them one at a time — producing **decisions, not deliverables** — until the fog is pushed back and the way is clear. Then it merges onto the main flow at **`/to-spec`** (or, if the effort turned out small enough, straight to **`/implement`**). Where **`/grill-with-docs`** sharpens an idea you can hold in one session, wayfinder is for the idea you can't.
## Codebase health
Not feature work — upkeep.
- **`/improve-codebase-architecture`** — run whenever you have a spare moment to keep the codebase good for agents to operate in. It surfaces **deepening opportunities**; picking one _generates an idea_ you can take into the main flow at `/grill-with-docs`. It's the survey that finds the candidates; **`/codebase-design`** (below) is the bench you design the chosen one on.
## Vocabulary underneath
Two model-invoked references that run *beneath* the other skills — each the single source of truth for its vocabulary. Reach for them directly when the **words**, not the process, are the problem; or let the skills above pull them in.
- **`/domain-modeling`** — sharpen the project's *domain* language: challenge a fuzzy term, resolve an overloaded word ("account" doing three jobs), record a hard-to-reverse decision as an ADR. It's the active discipline `/grill-with-docs` drives to keep `CONTEXT.md` a clean glossary.
- **`/codebase-design`** — the deep-module vocabulary (module, interface, depth, seam, adapter, leverage, locality) for designing a module's *shape*: a lot of behaviour behind a small interface at a clean seam. `/tdd` and `/improve-codebase-architecture` both speak it.
## Crossing sessions
- **`/handoff`** — when a thread is full or you need to branch off (e.g. into a `/prototype` session), this compacts the conversation into a markdown file. You don't continue in place — you **open a new session and reference that file** to carry the context across. It's the bridge between context windows, in either direction. Use it when you want a **fresh session** but need the **current conversation preserved**.
- **`/compact`** (built-in) — stay in the **same conversation**, letting the earlier turns be summarized. Use it at **intentional breaks between phases**, when you don't mind losing the verbatim history. Don't compact mid-phase — the agent can lose its way. `/handoff` forks; `/compact` continues.
## Standalone
Off the main flow entirely.
- **`/grill-me`** — the same relentless interview as `/grill-with-docs`, but for when you have **no codebase**. Stateless: it saves nothing locally, builds no `CONTEXT.md`. Reach for it to sharpen any plan or design that doesn't live in a repo.
- **`/prototype`** — a small, throwaway program that answers one design question: does this state model feel right, or what should this UI look like. Throwaway from day one — keep the answer, delete the code. It's the detour in step 2 of the main flow, but reach for it any time a design question is hard to settle on paper.
- **`/research`** — delegate reading legwork to a **background agent**: it investigates a question against **primary sources**, then leaves a cited Markdown file in the repo. Keep working while it reads. The file it produces is something to take *into* the main flow at `/grill-with-docs` — research feeds the thinking, it doesn't replace it.
- **`/teach`** — learn a concept over multiple sessions, using the current directory as a stateful workspace.
- **`/writing-great-skills`** — reference for writing and editing skills well.
## Precondition
**`/setup-matt-pocock-skills`** — run before your first engineering flow to configure the issue tracker, triage labels, and doc layout the other skills assume. Custom issue trackers also work.

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---
name: claude-handoff
description: Hand the current conversation off to a fresh background agent that picks up the work immediately.
argument-hint: "What will the next session be used for?"
disable-model-invocation: true
---
Write a handoff summary of the current conversation so a fresh agent can continue the work. Instead of saving it, launch a background agent seeded with the summary as its prompt: `claude --bg --name "<descriptive name>" "<handoff summary>"`. It starts in the current working directory and returns immediately; the user manages it with `claude agents`.
Always pass `-n`/`--name` with a descriptive name (e.g. `--name "Fix login bug"`) — it sets the display name shown in the job list, session picker, and terminal title.
Include a "suggested skills" section in the summary, which suggests skills that the agent should invoke.
Do not duplicate content already captured in other artifacts (PRDs, plans, ADRs, issues, commits, diffs). Reference them by path or URL instead.
Redact any sensitive information, such as API keys, passwords, or personally identifiable information — the summary becomes the agent's prompt.
If the user passed arguments, treat them as a description of what the next session will focus on and tailor the summary accordingly.

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---
name: code-review
description: Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
---
Two-axis review of the diff between `HEAD` and a fixed point the user supplies:
- **Standards** — does the code conform to this repo's documented coding standards?
- **Spec** — does the code faithfully implement the originating issue / PRD / spec?
Both axes run as **parallel sub-agents** so they don't pollute each other's context, then this skill aggregates their findings.
The issue tracker should have been provided to you — run `/setup-matt-pocock-skills` if `docs/agents/issue-tracker.md` is missing.
## Process
### 1. Pin the fixed point
Whatever the user said is the fixed point — a commit SHA, branch name, tag, `main`, `HEAD~5`, etc. If they didn't specify one, ask for it.
Capture the diff command once: `git diff <fixed-point>...HEAD` (three-dot, so the comparison is against the merge-base). Also note the list of commits via `git log <fixed-point>..HEAD --oneline`.
Before going further, confirm the fixed point resolves (`git rev-parse <fixed-point>`) and the diff is non-empty. A bad ref or empty diff should fail here — not inside two parallel sub-agents.
### 2. Identify the spec source
Look for the originating spec, in this order:
1. Issue references in the commit messages (`#123`, `Closes #45`, GitLab `!67`, etc.) — fetch via the workflow in `docs/agents/issue-tracker.md`.
2. A path the user passed as an argument.
3. A PRD/spec file under `docs/`, `specs/`, or `.scratch/` matching the branch name or feature.
4. If nothing is found, ask the user where the spec is. If they say there isn't one, the **Spec** sub-agent will skip and report "no spec available".
### 3. Identify the standards sources
Anything in the repo that documents how code should be written, such as `CODING_STANDARDS.md` or `CONTRIBUTING.md`.
On top of whatever the repo documents, the Standards axis always carries the **smell baseline** below — a fixed set of Fowler code smells (_Refactoring_, ch.3) that applies even when a repo documents nothing. Two rules bind it:
- **The repo overrides.** A documented repo standard always wins; where it endorses something the baseline would flag, suppress the smell.
- **Always a judgement call.** Each smell is a labelled heuristic ("possible Feature Envy"), never a hard violation — and, like any standard here, skip anything tooling already enforces.
Each smell reads *what it is**how to fix*; match it against the diff:
- **Mysterious Name** — a function, variable, or type whose name doesn't reveal what it does or holds. → rename it; if no honest name comes, the design's murky.
- **Duplicated Code** — the same logic shape appears in more than one hunk or file in the change. → extract the shared shape, call it from both.
- **Feature Envy** — a method that reaches into another object's data more than its own. → move the method onto the data it envies.
- **Data Clumps** — the same few fields or params keep travelling together (a type wanting to be born). → bundle them into one type, pass that.
- **Primitive Obsession** — a primitive or string standing in for a domain concept that deserves its own type. → give the concept its own small type.
- **Repeated Switches** — the same `switch`/`if`-cascade on the same type recurs across the change. → replace with polymorphism, or one map both sites share.
- **Shotgun Surgery** — one logical change forces scattered edits across many files in the diff. → gather what changes together into one module.
- **Divergent Change** — one file or module is edited for several unrelated reasons. → split so each module changes for one reason.
- **Speculative Generality** — abstraction, parameters, or hooks added for needs the spec doesn't have. → delete it; inline back until a real need shows.
- **Message Chains** — long `a.b().c().d()` navigation the caller shouldn't depend on. → hide the walk behind one method on the first object.
- **Middle Man** — a class or function that mostly just delegates onward. → cut it, call the real target direct.
- **Refused Bequest** — a subclass or implementer that ignores or overrides most of what it inherits. → drop the inheritance, use composition.
### 4. Spawn both sub-agents in parallel
Send a single message with two `Agent` tool calls. Use the `general-purpose` subagent for both.
**Standards sub-agent prompt** — include:
- The full diff command and commit list.
- The list of standards-source files you found in step 3, **plus the smell baseline from step 3** pasted in full — the sub-agent has no other access to it.
- The brief: "Report — per file/hunk where relevant — (a) every place the diff violates a documented standard: cite the standard (file + the rule); and (b) any baseline smell you spot: name it and quote the hunk. Distinguish hard violations from judgement calls — documented-standard breaches can be hard, but baseline smells are always judgement calls, and a documented repo standard overrides the baseline. Skip anything tooling enforces. Under 400 words."
**Spec sub-agent prompt** — include:
- The diff command and commit list.
- The path or fetched contents of the spec.
- The brief: "Report: (a) requirements the spec asked for that are missing or partial; (b) behaviour in the diff that wasn't asked for (scope creep); (c) requirements that look implemented but where the implementation looks wrong. Quote the spec line for each finding. Under 400 words."
If the spec is missing, skip the Spec sub-agent and note this in the final report.
### 5. Aggregate
Present the two reports under `## Standards` and `## Spec` headings, verbatim or lightly cleaned. Do **not** merge or rerank findings — the two axes are deliberately separate (see _Why two axes_).
End with a one-line summary: total findings per axis, and the worst issue _within each axis_ (if any). Don't pick a single winner across axes — that's the reranking the separation exists to prevent.
## Why two axes
A change can pass one axis and fail the other:
- Code that follows every standard but implements the wrong thing → **Standards pass, Spec fail.**
- Code that does exactly what the issue asked but breaks the project's conventions → **Spec pass, Standards fail.**
Reporting them separately stops one axis from masking the other.

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# Deepening
How to deepen a cluster of shallow modules safely, given its dependencies. Assumes the vocabulary in [SKILL.md](SKILL.md) — **module**, **interface**, **seam**, **adapter**.
## Dependency categories
When assessing a candidate for deepening, classify its dependencies. The category determines how the deepened module is tested across its seam.
### 1. In-process
Pure computation, in-memory state, no I/O. Always deepenable — merge the modules and test through the new interface directly. No adapter needed.
### 2. Local-substitutable
Dependencies that have local test stand-ins (PGLite for Postgres, in-memory filesystem). Deepenable if the stand-in exists. The deepened module is tested with the stand-in running in the test suite. The seam is internal; no port at the module's external interface.
### 3. Remote but owned (Ports & Adapters)
Your own services across a network boundary (microservices, internal APIs). Define a **port** (interface) at the seam. The deep module owns the logic; the transport is injected as an **adapter**. Tests use an in-memory adapter. Production uses an HTTP/gRPC/queue adapter.
Recommendation shape: *"Define a port at the seam, implement an HTTP adapter for production and an in-memory adapter for testing, so the logic sits in one deep module even though it's deployed across a network."*
### 4. True external (Mock)
Third-party services (Stripe, Twilio, etc.) you don't control. The deepened module takes the external dependency as an injected port; tests provide a mock adapter.
## Seam discipline
- **One adapter means a hypothetical seam. Two adapters means a real one.** Don't introduce a port unless at least two adapters are justified (typically production + test). A single-adapter seam is just indirection.
- **Internal seams vs external seams.** A deep module can have internal seams (private to its implementation, used by its own tests) as well as the external seam at its interface. Don't expose internal seams through the interface just because tests use them.
## Testing strategy: replace, don't layer
- Old unit tests on shallow modules become waste once tests at the deepened module's interface exist — delete them.
- Write new tests at the deepened module's interface. The **interface is the test surface**.
- Tests assert on observable outcomes through the interface, not internal state.
- Tests should survive internal refactors — they describe behaviour, not implementation. If a test has to change when the implementation changes, it's testing past the interface.

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# Design It Twice
When the user wants to explore alternative interfaces for a chosen deepening candidate, use this parallel sub-agent pattern. Based on "Design It Twice" (Ousterhout) — your first idea is unlikely to be the best.
Uses the vocabulary in [SKILL.md](SKILL.md) — **module**, **interface**, **seam**, **adapter**, **leverage**.
## Process
### 1. Frame the problem space
Before spawning sub-agents, write a user-facing explanation of the problem space for the chosen candidate:
- The constraints any new interface would need to satisfy
- The dependencies it would rely on, and which category they fall into (see [DEEPENING.md](DEEPENING.md))
- A rough illustrative code sketch to ground the constraints — not a proposal, just a way to make the constraints concrete
Show this to the user, then immediately proceed to Step 2. The user reads and thinks while the sub-agents work in parallel.
### 2. Spawn sub-agents
Spawn 3+ sub-agents in parallel using the Agent tool. Each must produce a **radically different** interface for the deepened module.
Prompt each sub-agent with a separate technical brief (file paths, coupling details, dependency category from [DEEPENING.md](DEEPENING.md), what sits behind the seam). The brief is independent of the user-facing problem-space explanation in Step 1. Give each agent a different design constraint:
- Agent 1: "Minimize the interface — aim for 13 entry points max. Maximise leverage per entry point."
- Agent 2: "Maximise flexibility — support many use cases and extension."
- Agent 3: "Optimise for the most common caller — make the default case trivial."
- Agent 4 (if applicable): "Design around ports & adapters for cross-seam dependencies."
Include both [SKILL.md](SKILL.md) vocabulary and CONTEXT.md vocabulary in the brief so each sub-agent names things consistently with the architecture language and the project's domain language.
Each sub-agent outputs:
1. Interface (types, methods, params — plus invariants, ordering, error modes)
2. Usage example showing how callers use it
3. What the implementation hides behind the seam
4. Dependency strategy and adapters (see [DEEPENING.md](DEEPENING.md))
5. Trade-offs — where leverage is high, where it's thin
### 3. Present and compare
Present designs sequentially so the user can absorb each one, then compare them in prose. Contrast by **depth** (leverage at the interface), **locality** (where change concentrates), and **seam placement**.
After comparing, give your own recommendation: which design you think is strongest and why. If elements from different designs would combine well, propose a hybrid. Be opinionated — the user wants a strong read, not a menu.

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---
name: codebase-design
description: Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
---
# Codebase Design
Design **deep modules**: a lot of behaviour behind a small interface, placed at a clean seam, testable through that interface. Use this language and these principles wherever code is being designed or restructured. The aim is leverage for callers, locality for maintainers, and testability for everyone.
## Glossary
Use these terms exactly — don't substitute "component," "service," "API," or "boundary." Consistent language is the whole point.
**Module** — anything with an interface and an implementation. Deliberately scale-agnostic: a function, class, package, or tier-spanning slice. _Avoid_: unit, component, service.
**Interface** — everything a caller must know to use the module correctly: the type signature, but also invariants, ordering constraints, error modes, required configuration, and performance characteristics. _Avoid_: API, signature (too narrow — they refer only to the type-level surface).
**Implementation** — what's inside a module, its body of code. Distinct from **Adapter**: a thing can be a small adapter with a large implementation (a Postgres repo) or a large adapter with a small implementation (an in-memory fake). Reach for "adapter" when the seam is the topic; "implementation" otherwise.
**Depth** — leverage at the interface: the amount of behaviour a caller (or test) can exercise per unit of interface they have to learn. A module is **deep** when a large amount of behaviour sits behind a small interface, **shallow** when the interface is nearly as complex as the implementation.
**Seam** _(Michael Feathers)_ — a place where you can alter behaviour without editing in that place; the *location* at which a module's interface lives. Where to put the seam is its own design decision, distinct from what goes behind it. _Avoid_: boundary (overloaded with DDD's bounded context).
**Adapter** — a concrete thing that satisfies an interface at a seam. Describes *role* (what slot it fills), not substance (what's inside).
**Leverage** — what callers get from depth: more capability per unit of interface they learn. One implementation pays back across N call sites and M tests.
**Locality** — what maintainers get from depth: change, bugs, knowledge, and verification concentrate in one place rather than spreading across callers. Fix once, fixed everywhere.
## Deep vs shallow
**Deep module** = small interface + lots of implementation:
```
┌─────────────────────┐
│ Small Interface │ ← Few methods, simple params
├─────────────────────┤
│ │
│ Deep Implementation│ ← Complex logic hidden
│ │
└─────────────────────┘
```
**Shallow module** = large interface + little implementation (avoid):
```
┌─────────────────────────────────┐
│ Large Interface │ ← Many methods, complex params
├─────────────────────────────────┤
│ Thin Implementation │ ← Just passes through
└─────────────────────────────────┘
```
When designing an interface, ask:
- Can I reduce the number of methods?
- Can I simplify the parameters?
- Can I hide more complexity inside?
## Principles
- **Depth is a property of the interface, not the implementation.** A deep module can be internally composed of small, mockable, swappable parts — they just aren't part of the interface. A module can have **internal seams** (private to its implementation, used by its own tests) as well as the **external seam** at its interface.
- **The deletion test.** Imagine deleting the module. If complexity vanishes, it was a pass-through. If complexity reappears across N callers, it was earning its keep.
- **The interface is the test surface.** Callers and tests cross the same seam. If you want to test *past* the interface, the module is probably the wrong shape.
- **One adapter means a hypothetical seam. Two adapters means a real one.** Don't introduce a seam unless something actually varies across it.
## Designing for testability
Good interfaces make testing natural:
1. **Accept dependencies, don't create them.**
```typescript
// Testable
function processOrder(order, paymentGateway) {}
// Hard to test
function processOrder(order) {
const gateway = new StripeGateway();
}
```
2. **Return results, don't produce side effects.**
```typescript
// Testable
function calculateDiscount(cart): Discount {}
// Hard to test
function applyDiscount(cart): void {
cart.total -= discount;
}
```
3. **Small surface area.** Fewer methods = fewer tests needed. Fewer params = simpler test setup.
## Relationships
- A **Module** has exactly one **Interface** (the surface it presents to callers and tests).
- **Depth** is a property of a **Module**, measured against its **Interface**.
- A **Seam** is where a **Module**'s **Interface** lives.
- An **Adapter** sits at a **Seam** and satisfies the **Interface**.
- **Depth** produces **Leverage** for callers and **Locality** for maintainers.
## Rejected framings
- **Depth as ratio of implementation-lines to interface-lines** (Ousterhout): rewards padding the implementation. We use depth-as-leverage instead.
- **"Interface" as the TypeScript `interface` keyword or a class's public methods**: too narrow — interface here includes every fact a caller must know.
- **"Boundary"**: overloaded with DDD's bounded context. Say **seam** or **interface**.
## Going deeper
- **Deepening a cluster given its dependencies** — see [DEEPENING.md](DEEPENING.md): dependency categories, seam discipline, and replace-don't-layer testing.
- **Exploring alternative interfaces** — see [DESIGN-IT-TWICE.md](DESIGN-IT-TWICE.md): spin up parallel sub-agents to design the interface several radically different ways, then compare on depth, locality, and seam placement.

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---
name: decision-mapping
description: Turn a loose idea into a sequenced map of investigation tickets, then drive them to resolution one at a time.
disable-model-invocation: true
---
This skill is invoked when a loose idea requires more than one agent session to turn into a plan. It creates a stateful decision map in a markdown file, and drives the user through a sequence of tickets to resolve the open questions - which may require either prototyping, research or discussion.
## The Decision Map
The decision map is a single compact Markdown file, one per planning effort, git-tracked alongside the project. It is the canonical artifact — the **whole map is loaded as context into every session**, so it must stay compact.
Assets created during tickets should be linked to from the map, not duplicated within it.
### Structure
Numbered entries ("tickets"), each its own section keyed by its number:
```markdown
## #1: Relational Or Non-Relational Database?
Blocked by: #<ticket-number>, #<ticket-number>
Type: Research | Prototype | Grilling
### Question
<question-here>
### Answer
<answer-here>
```
Each ticket must be sized to one 100K token agent session.
## Ticket Types
There are three types of tickets:
- **Research**: Reading documentation, third-party API's, or local resources like knowledge bases. Creates a markdown summary as an asset. Use this when knowledge outside the current working directory is required.
- **Prototype**: Writing UI or logic code to test a hypothesis, or to explore a design space. Uses the /prototype skill. Creates a prototype as an asset. Use this when "how should it look" or "how should it behave" is the key question.
- **Grilling**: Conversation with the agent. Uses the /grilling and /domain-modelling skills. Asks one question at a time. The default case.
## Fog of war
The map is _deliberately_ incomplete beyond the frontier. Your job is to investigate the frontier, and to resolve tickets in order to push the frontier forward. Push back the fog of war, one node at a time.
At some point, the fog of war should have been pushed back far enough that the path to the finish line is clear. At that point, no more tickets will be required and the decision map can be considered 'done'.
## Invocation
There are two ways this skill can be invoked: **bootstrap** and **resume**.
### Bootstrap
User invokes with a loose idea.
1. Run a /grilling + /domain-modelling session to surface the open decisions. Ask one question at a time.
2. Write a new decision map — mostly fog, frontier identified, trivially-decidable entries resolved inline.
3. Stop. Map-building is one session's work; do not also resolve tickets.
### Resume
User invokes with a path to an existing map and a ticket number.
1. Load the **whole map** as context.
2. Run a session to resolve the ticket, invoking skills as needed. If in doubt, use `/grilling` and `/domain-modelling`.
3. Record what the session resolved in the ticket's body.
4. Add newly-discovered tickets (with correct `blocked_by` edges).
5. Stop.
If the decisions made invalidate other parts of the map, update or delete those nodes.
## Parallelism
The user may choose to run tickets in parallel, so expect other agents to make changes to the map.
## Skipping The Decision Map
Many times, the initial grilling will result in no fog of war. No unresolved tickets. Nothing to do, except implement.
In those situations, you should offer the user the chance to skip the decision map - since the decision map is only needed if multi-session decisions need to be made.
If they skip it, you should recommend either implementing directly or using `/to-prd` to schedule a multi-session implementation.

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---
name: design-an-interface
description: Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
---
# Design an Interface
Based on "Design It Twice" from "A Philosophy of Software Design": your first idea is unlikely to be the best. Generate multiple radically different designs, then compare.
## Workflow
### 1. Gather Requirements
Before designing, understand:
- [ ] What problem does this module solve?
- [ ] Who are the callers? (other modules, external users, tests)
- [ ] What are the key operations?
- [ ] Any constraints? (performance, compatibility, existing patterns)
- [ ] What should be hidden inside vs exposed?
Ask: "What does this module need to do? Who will use it?"
### 2. Generate Designs (Parallel Sub-Agents)
Spawn 3+ sub-agents simultaneously using Task tool. Each must produce a **radically different** approach.
```
Prompt template for each sub-agent:
Design an interface for: [module description]
Requirements: [gathered requirements]
Constraints for this design: [assign a different constraint to each agent]
- Agent 1: "Minimize method count - aim for 1-3 methods max"
- Agent 2: "Maximize flexibility - support many use cases"
- Agent 3: "Optimize for the most common case"
- Agent 4: "Take inspiration from [specific paradigm/library]"
Output format:
1. Interface signature (types/methods)
2. Usage example (how caller uses it)
3. What this design hides internally
4. Trade-offs of this approach
```
### 3. Present Designs
Show each design with:
1. **Interface signature** - types, methods, params
2. **Usage examples** - how callers actually use it in practice
3. **What it hides** - complexity kept internal
Present designs sequentially so user can absorb each approach before comparison.
### 4. Compare Designs
After showing all designs, compare them on:
- **Interface simplicity**: fewer methods, simpler params
- **General-purpose vs specialized**: flexibility vs focus
- **Implementation efficiency**: does shape allow efficient internals?
- **Depth**: small interface hiding significant complexity (good) vs large interface with thin implementation (bad)
- **Ease of correct use** vs **ease of misuse**
Discuss trade-offs in prose, not tables. Highlight where designs diverge most.
### 5. Synthesize
Often the best design combines insights from multiple options. Ask:
- "Which design best fits your primary use case?"
- "Any elements from other designs worth incorporating?"
## Evaluation Criteria
From "A Philosophy of Software Design":
**Interface simplicity**: Fewer methods, simpler params = easier to learn and use correctly.
**General-purpose**: Can handle future use cases without changes. But beware over-generalization.
**Implementation efficiency**: Does interface shape allow efficient implementation? Or force awkward internals?
**Depth**: Small interface hiding significant complexity = deep module (good). Large interface with thin implementation = shallow module (avoid).
## Anti-Patterns
- Don't let sub-agents produce similar designs - enforce radical difference
- Don't skip comparison - the value is in contrast
- Don't implement - this is purely about interface shape
- Don't evaluate based on implementation effort

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---
name: diagnosing-bugs
description: Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
---
# Diagnosing Bugs
A discipline for hard bugs. Skip phases only when explicitly justified.
When exploring the codebase, read `CONTEXT.md` (if it exists) to get a clear mental model of the relevant modules, and check ADRs in the area you're touching.
## Phase 1 — Build a feedback loop
**This is the skill.** Everything else is mechanical. If you have a **tight** pass/fail signal for the bug — one that goes red on _this_ bug — you will find the cause; bisection, hypothesis-testing, and instrumentation all just consume it. If you don't have one, no amount of staring at code will save you.
Spend disproportionate effort here. **Be aggressive. Be creative. Refuse to give up.**
### Ways to construct one — try them in roughly this order
1. **Failing test** at whatever seam reaches the bug — unit, integration, e2e.
2. **Curl / HTTP script** against a running dev server.
3. **CLI invocation** with a fixture input, diffing stdout against a known-good snapshot.
4. **Headless browser script** (Playwright / Puppeteer) — drives the UI, asserts on DOM/console/network.
5. **Replay a captured trace.** Save a real network request / payload / event log to disk; replay it through the code path in isolation.
6. **Throwaway harness.** Spin up a minimal subset of the system (one service, mocked deps) that exercises the bug code path with a single function call.
7. **Property / fuzz loop.** If the bug is "sometimes wrong output", run 1000 random inputs and look for the failure mode.
8. **Bisection harness.** If the bug appeared between two known states (commit, dataset, version), automate "boot at state X, check, repeat" so you can `git bisect run` it.
9. **Differential loop.** Run the same input through old-version vs new-version (or two configs) and diff outputs.
10. **HITL bash script.** Last resort. If a human must click, drive _them_ with `scripts/hitl-loop.template.sh` so the loop is still structured. Captured output feeds back to you.
Build the right feedback loop, and the bug is 90% fixed.
### Tighten the loop
Treat the loop as a product. Once you have _a_ loop, **tighten** it:
- Can I make it faster? (Cache setup, skip unrelated init, narrow the test scope.)
- Can I make the signal sharper? (Assert on the specific symptom, not "didn't crash".)
- Can I make it more deterministic? (Pin time, seed RNG, isolate filesystem, freeze network.)
A 30-second flaky loop is barely better than no loop; a 2-second deterministic one is tight — a debugging superpower.
### Non-deterministic bugs
The goal is not a clean repro but a **higher reproduction rate**. Loop the trigger 100×, parallelise, add stress, narrow timing windows, inject sleeps. A 50%-flake bug is debuggable; 1% is not — keep raising the rate until it's debuggable.
### When you genuinely cannot build a loop
Stop and say so explicitly. List what you tried. Ask the user for: (a) access to whatever environment reproduces it, (b) a captured artifact (HAR file, log dump, core dump, screen recording with timestamps), or (c) permission to add temporary production instrumentation. Do **not** proceed to hypothesise without a loop.
### Completion criterion — a tight loop that goes red
Phase 1 is done when the loop is **tight** and **red-capable**: you can name **one command** — a script path, a test invocation, a curl — that you have **already run at least once** (paste the invocation and its output), and that is:
- [ ] **Red-capable** — it drives the actual bug code path and asserts the **user's exact symptom**, so it can go red on this bug and green once fixed. Not "runs without erroring" — it must be able to _catch this specific bug_.
- [ ] **Deterministic** — same verdict every run (flaky bugs: a pinned, high reproduction rate, per above).
- [ ] **Fast** — seconds, not minutes.
- [ ] **Agent-runnable** — you can run it unattended; a human in the loop only via `scripts/hitl-loop.template.sh`.
If you catch yourself reading code to build a theory before this command exists, **stop — jumping straight to a hypothesis is the exact failure this skill prevents.** No red-capable command, no Phase 2.
## Phase 2 — Reproduce + minimise
Run the loop. Watch it go red — the bug appears.
Confirm:
- [ ] The loop produces the failure mode the **user** described — not a different failure that happens to be nearby. Wrong bug = wrong fix.
- [ ] The failure is reproducible across multiple runs (or, for non-deterministic bugs, reproducible at a high enough rate to debug against).
- [ ] You have captured the exact symptom (error message, wrong output, slow timing) so later phases can verify the fix actually addresses it.
### Minimise
Once it's red, shrink the repro to the **smallest scenario that still goes red**. Cut inputs, callers, config, data, and steps **one at a time**, re-running the loop after each cut — keep only what's load-bearing for the failure.
Why bother: a minimal repro shrinks the hypothesis space in Phase 3 (fewer moving parts left to suspect) and becomes the clean regression test in Phase 5.
Done when **every remaining element is load-bearing** — removing any one of them makes the loop go green.
Do not proceed until you have reproduced **and** minimised.
## Phase 3 — Hypothesise
Generate **35 ranked hypotheses** before testing any of them. Single-hypothesis generation anchors on the first plausible idea.
Each hypothesis must be **falsifiable**: state the prediction it makes.
> Format: "If <X> is the cause, then <changing Y> will make the bug disappear / <changing Z> will make it worse."
If you cannot state the prediction, the hypothesis is a vibe — discard or sharpen it.
**Show the ranked list to the user before testing.** They often have domain knowledge that re-ranks instantly ("we just deployed a change to #3"), or know hypotheses they've already ruled out. Cheap checkpoint, big time saver. Don't block on it — proceed with your ranking if the user is AFK.
## Phase 4 — Instrument
Each probe must map to a specific prediction from Phase 3. **Change one variable at a time.**
Tool preference:
1. **Debugger / REPL inspection** if the env supports it. One breakpoint beats ten logs.
2. **Targeted logs** at the boundaries that distinguish hypotheses.
3. Never "log everything and grep".
**Tag every debug log** with a unique prefix, e.g. `[DEBUG-a4f2]`. Cleanup at the end becomes a single grep. Untagged logs survive; tagged logs die.
**Perf branch.** For performance regressions, logs are usually wrong. Instead: establish a baseline measurement (timing harness, `performance.now()`, profiler, query plan), then bisect. Measure first, fix second.
## Phase 5 — Fix + regression test
Write the regression test **before the fix** — but only if there is a **correct seam** for it.
A correct seam is one where the test exercises the **real bug pattern** as it occurs at the call site. If the only available seam is too shallow (single-caller test when the bug needs multiple callers, unit test that can't replicate the chain that triggered the bug), a regression test there gives false confidence.
**If no correct seam exists, that itself is the finding.** Note it. The codebase architecture is preventing the bug from being locked down. Flag this for the next phase.
If a correct seam exists:
1. Turn the minimised repro into a failing test at that seam.
2. Watch it fail.
3. Apply the fix.
4. Watch it pass.
5. Re-run the Phase 1 feedback loop against the original (un-minimised) scenario.
## Phase 6 — Cleanup + post-mortem
Required before declaring done:
- [ ] Original repro no longer reproduces (re-run the Phase 1 loop)
- [ ] Regression test passes (or absence of seam is documented)
- [ ] All `[DEBUG-...]` instrumentation removed (`grep` the prefix)
- [ ] Throwaway prototypes deleted (or moved to a clearly-marked debug location)
- [ ] The hypothesis that turned out correct is stated in the commit / PR message — so the next debugger learns
**Then ask: what would have prevented this bug?** If the answer involves architectural change (no good test seam, tangled callers, hidden coupling) hand off to the `/improve-codebase-architecture` skill with the specifics. Make the recommendation **after** the fix is in, not before — you have more information now than when you started.

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#!/usr/bin/env bash
# Human-in-the-loop reproduction loop.
# Copy this file, edit the steps below, and run it.
# The agent runs the script; the user follows prompts in their terminal.
#
# Usage:
# bash hitl-loop.template.sh
#
# Two helpers:
# step "<instruction>" → show instruction, wait for Enter
# capture VAR "<question>" → show question, read response into VAR
#
# At the end, captured values are printed as KEY=VALUE for the agent to parse.
set -euo pipefail
step() {
printf '\n>>> %s\n' "$1"
read -r -p " [Enter when done] " _
}
capture() {
local var="$1" question="$2" answer
printf '\n>>> %s\n' "$question"
read -r -p " > " answer
printf -v "$var" '%s' "$answer"
}
# --- edit below ---------------------------------------------------------
step "Open the app at http://localhost:3000 and sign in."
capture ERRORED "Click the 'Export' button. Did it throw an error? (y/n)"
capture ERROR_MSG "Paste the error message (or 'none'):"
# --- edit above ---------------------------------------------------------
printf '\n--- Captured ---\n'
printf 'ERRORED=%s\n' "$ERRORED"
printf 'ERROR_MSG=%s\n' "$ERROR_MSG"

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# ADR Format
ADRs live in `docs/adr/` and use sequential numbering: `0001-slug.md`, `0002-slug.md`, etc.
Create the `docs/adr/` directory lazily — only when the first ADR is needed.
## Template
```md
# {Short title of the decision}
{1-3 sentences: what's the context, what did we decide, and why.}
```
That's it. An ADR can be a single paragraph. The value is in recording *that* a decision was made and *why* — not in filling out sections.
## Optional sections
Only include these when they add genuine value. Most ADRs won't need them.
- **Status** frontmatter (`proposed | accepted | deprecated | superseded by ADR-NNNN`) — useful when decisions are revisited
- **Considered Options** — only when the rejected alternatives are worth remembering
- **Consequences** — only when non-obvious downstream effects need to be called out
## Numbering
Scan `docs/adr/` for the highest existing number and increment by one.
## When to offer an ADR
All three of these must be true:
1. **Hard to reverse** — the cost of changing your mind later is meaningful
2. **Surprising without context** — a future reader will look at the code and wonder "why on earth did they do it this way?"
3. **The result of a real trade-off** — there were genuine alternatives and you picked one for specific reasons
If a decision is easy to reverse, skip it — you'll just reverse it. If it's not surprising, nobody will wonder why. If there was no real alternative, there's nothing to record beyond "we did the obvious thing."
### What qualifies
- **Architectural shape.** "We're using a monorepo." "The write model is event-sourced, the read model is projected into Postgres."
- **Integration patterns between contexts.** "Ordering and Billing communicate via domain events, not synchronous HTTP."
- **Technology choices that carry lock-in.** Database, message bus, auth provider, deployment target. Not every library — just the ones that would take a quarter to swap out.
- **Boundary and scope decisions.** "Customer data is owned by the Customer context; other contexts reference it by ID only." The explicit no-s are as valuable as the yes-s.
- **Deliberate deviations from the obvious path.** "We're using manual SQL instead of an ORM because X." Anything where a reasonable reader would assume the opposite. These stop the next engineer from "fixing" something that was deliberate.
- **Constraints not visible in the code.** "We can't use AWS because of compliance requirements." "Response times must be under 200ms because of the partner API contract."
- **Rejected alternatives when the rejection is non-obvious.** If you considered GraphQL and picked REST for subtle reasons, record it — otherwise someone will suggest GraphQL again in six months.

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# CONTEXT.md Format
## Structure
```md
# {Context Name}
{One or two sentence description of what this context is and why it exists.}
## Language
**Order**:
{A one or two sentence description of the term}
_Avoid_: Purchase, transaction
**Invoice**:
A request for payment sent to a customer after delivery.
_Avoid_: Bill, payment request
**Customer**:
A person or organization that places orders.
_Avoid_: Client, buyer, account
```
## Rules
- **Be opinionated.** When multiple words exist for the same concept, pick the best one and list the others under `_Avoid_`.
- **Keep definitions tight.** One or two sentences max. Define what it IS, not what it does.
- **Only include terms specific to this project's context.** General programming concepts (timeouts, error types, utility patterns) don't belong even if the project uses them extensively. Before adding a term, ask: is this a concept unique to this context, or a general programming concept? Only the former belongs.
- **Group terms under subheadings** when natural clusters emerge. If all terms belong to a single cohesive area, a flat list is fine.
## Single vs multi-context repos
**Single context (most repos):** One `CONTEXT.md` at the repo root.
**Multiple contexts:** A `CONTEXT-MAP.md` at the repo root lists the contexts, where they live, and how they relate to each other:
```md
# Context Map
## Contexts
- [Ordering](./src/ordering/CONTEXT.md) — receives and tracks customer orders
- [Billing](./src/billing/CONTEXT.md) — generates invoices and processes payments
- [Fulfillment](./src/fulfillment/CONTEXT.md) — manages warehouse picking and shipping
## Relationships
- **Ordering → Fulfillment**: Ordering emits `OrderPlaced` events; Fulfillment consumes them to start picking
- **Fulfillment → Billing**: Fulfillment emits `ShipmentDispatched` events; Billing consumes them to generate invoices
- **Ordering ↔ Billing**: Shared types for `CustomerId` and `Money`
```
The skill infers which structure applies:
- If `CONTEXT-MAP.md` exists, read it to find contexts
- If only a root `CONTEXT.md` exists, single context
- If neither exists, create a root `CONTEXT.md` lazily when the first term is resolved
When multiple contexts exist, infer which one the current topic relates to. If unclear, ask.

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---
name: domain-modeling
description: Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.
---
# Domain Modeling
Actively build and sharpen the project's domain model as you design. This is the *active* discipline — challenging terms, inventing edge-case scenarios, and writing the glossary and decisions down the moment they crystallise. (Merely *reading* `CONTEXT.md` for vocabulary is not this skill — that's a one-line habit any skill can do. This skill is for when you're changing the model, not just consuming it.)
## File structure
Most repos have a single context:
```
/
├── CONTEXT.md
├── docs/
│ └── adr/
│ ├── 0001-event-sourced-orders.md
│ └── 0002-postgres-for-write-model.md
└── src/
```
If a `CONTEXT-MAP.md` exists at the root, the repo has multiple contexts. The map points to where each one lives:
```
/
├── CONTEXT-MAP.md
├── docs/
│ └── adr/ ← system-wide decisions
├── src/
│ ├── ordering/
│ │ ├── CONTEXT.md
│ │ └── docs/adr/ ← context-specific decisions
│ └── billing/
│ ├── CONTEXT.md
│ └── docs/adr/
```
Create files lazily — only when you have something to write. If no `CONTEXT.md` exists, create one when the first term is resolved. If no `docs/adr/` exists, create it when the first ADR is needed.
## During the session
### Challenge against the glossary
When the user uses a term that conflicts with the existing language in `CONTEXT.md`, call it out immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y — which is it?"
### Sharpen fuzzy language
When the user uses vague or overloaded terms, propose a precise canonical term. "You're saying 'account' — do you mean the Customer or the User? Those are different things."
### Discuss concrete scenarios
When domain relationships are being discussed, stress-test them with specific scenarios. Invent scenarios that probe edge cases and force the user to be precise about the boundaries between concepts.
### Cross-reference with code
When the user states how something works, check whether the code agrees. If you find a contradiction, surface it: "Your code cancels entire Orders, but you just said partial cancellation is possible — which is right?"
### Update CONTEXT.md inline
When a term is resolved, update `CONTEXT.md` right there. Don't batch these up — capture them as they happen. Use the format in [CONTEXT-FORMAT.md](./CONTEXT-FORMAT.md).
`CONTEXT.md` should be totally devoid of implementation details. Do not treat `CONTEXT.md` as a spec, a scratch pad, or a repository for implementation decisions. It is a glossary and nothing else.
### Offer ADRs sparingly
Only offer to create an ADR when all three are true:
1. **Hard to reverse** — the cost of changing your mind later is meaningful
2. **Surprising without context** — a future reader will wonder "why did they do it this way?"
3. **The result of a real trade-off** — there were genuine alternatives and you picked one for specific reasons
If any of the three is missing, skip the ADR. Use the format in [ADR-FORMAT.md](./ADR-FORMAT.md).

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---
name: edit-article
description: Edit and improve articles by restructuring sections, improving clarity, and tightening prose. Use when user wants to edit, revise, or improve an article draft.
disable-model-invocation: true
---
1. First, divide the article into sections based on its headings. Think about the main points you want to make during those sections.
Consider that information is a directed acyclic graph, and that pieces of information can depend on other pieces of information. Make sure that the order of the sections and their contents respects these dependencies.
Confirm the sections with the user.
2. For each section:
2a. Rewrite the section to improve clarity, coherence, and flow. Use maximum 240 characters per paragraph.

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---
name: git-guardrails-claude-code
description: Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, branch -D, etc.) before they execute. Use when user wants to prevent destructive git operations, add git safety hooks, or block git push/reset in Claude Code.
---
# Setup Git Guardrails
Sets up a PreToolUse hook that intercepts and blocks dangerous git commands before Claude executes them.
## What Gets Blocked
- `git push` (all variants including `--force`)
- `git reset --hard`
- `git clean -f` / `git clean -fd`
- `git branch -D`
- `git checkout .` / `git restore .`
When blocked, Claude sees a message telling it that it does not have authority to access these commands.
## Steps
### 1. Ask scope
Ask the user: install for **this project only** (`.claude/settings.json`) or **all projects** (`~/.claude/settings.json`)?
### 2. Copy the hook script
The bundled script is at: [scripts/block-dangerous-git.sh](scripts/block-dangerous-git.sh)
Copy it to the target location based on scope:
- **Project**: `.claude/hooks/block-dangerous-git.sh`
- **Global**: `~/.claude/hooks/block-dangerous-git.sh`
Make it executable with `chmod +x`.
### 3. Add hook to settings
Add to the appropriate settings file:
**Project** (`.claude/settings.json`):
```json
{
"hooks": {
"PreToolUse": [
{
"matcher": "Bash",
"hooks": [
{
"type": "command",
"command": "\"$CLAUDE_PROJECT_DIR\"/.claude/hooks/block-dangerous-git.sh"
}
]
}
]
}
}
```
**Global** (`~/.claude/settings.json`):
```json
{
"hooks": {
"PreToolUse": [
{
"matcher": "Bash",
"hooks": [
{
"type": "command",
"command": "~/.claude/hooks/block-dangerous-git.sh"
}
]
}
]
}
}
```
If the settings file already exists, merge the hook into existing `hooks.PreToolUse` array — don't overwrite other settings.
### 4. Ask about customization
Ask if user wants to add or remove any patterns from the blocked list. Edit the copied script accordingly.
### 5. Verify
Run a quick test:
```bash
echo '{"tool_input":{"command":"git push origin main"}}' | <path-to-script>
```
Should exit with code 2 and print a BLOCKED message to stderr.

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#!/bin/bash
INPUT=$(cat)
COMMAND=$(echo "$INPUT" | jq -r '.tool_input.command')
DANGEROUS_PATTERNS=(
"git push"
"git reset --hard"
"git clean -fd"
"git clean -f"
"git branch -D"
"git checkout \."
"git restore \."
"push --force"
"reset --hard"
)
for pattern in "${DANGEROUS_PATTERNS[@]}"; do
if echo "$COMMAND" | grep -qE "$pattern"; then
echo "BLOCKED: '$COMMAND' matches dangerous pattern '$pattern'. The user has prevented you from doing this." >&2
exit 2
fi
done
exit 0

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---
name: grill-me
description: A relentless interview to sharpen a plan or design.
disable-model-invocation: true
---
Run a `/grilling` session.

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---
name: grill-with-docs
description: A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
disable-model-invocation: true
---
Run a `/grilling` session, using the `/domain-modeling` skill.

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---
name: grilling
description: Grill the user relentlessly about a plan or design. Use when the user wants to stress-test a plan before building, or uses any 'grill' trigger phrases.
---
Interview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.
Ask the questions one at a time, waiting for feedback on each question before continuing. Asking multiple questions at once is bewildering.
If a *fact* can be found by exploring the codebase, look it up rather than asking me. The *decisions*, though, are mine — put each one to me and wait for my answer.
Do not enact the plan until I confirm we have reached a shared understanding.

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---
name: handoff
description: Compact the current conversation into a handoff document for another agent to pick up.
argument-hint: "What will the next session be used for?"
disable-model-invocation: true
---
Write a handoff document summarising the current conversation so a fresh agent can continue the work. Save to the temporary directory of the user's OS - not the current workspace.
Include a "suggested skills" section in the document, which suggests skills that the agent should invoke.
Do not duplicate content already captured in other artifacts (specs, plans, ADRs, issues, commits, diffs). Reference them by path or URL instead.
Redact any sensitive information, such as API keys, passwords, or personally identifiable information.
If the user passed arguments, treat them as a description of what the next session will focus on and tailor the doc accordingly.

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---
name: implement
description: "Implement a piece of work based on a spec or set of tickets."
disable-model-invocation: true
---
Implement the work described by the user in the spec or tickets.
Use /tdd where possible, at pre-agreed seams.
Run typechecking regularly, single test files regularly, and the full test suite once at the end.
Once done, use /code-review to review the work.
Commit your work to the current branch.

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# HTML Report Format
The architectural review is rendered as a single self-contained HTML file in the OS temp directory. Tailwind and Mermaid both come from CDNs. Mermaid handles graph-shaped diagrams reliably; hand-built divs and inline SVG handle the more editorial visuals (mass diagrams, cross-sections). Mix the two — don't lean on Mermaid for everything, it'll start to look generic.
## Scaffold
```html
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<title>Architecture review — {{repo name}}</title>
<script src="https://cdn.tailwindcss.com"></script>
<script type="module">
import mermaid from "https://cdn.jsdelivr.net/npm/mermaid@11/dist/mermaid.esm.min.mjs";
mermaid.initialize({ startOnLoad: true, theme: "neutral", securityLevel: "loose" });
</script>
<style>
/* small custom layer for things Tailwind doesn't cover cleanly:
dashed seam lines, hand-drawn-feeling arrow heads, etc. */
.seam { stroke-dasharray: 4 4; }
.leak { stroke: #dc2626; }
.deep { background: linear-gradient(135deg, #0f172a, #1e293b); }
</style>
</head>
<body class="bg-stone-50 text-slate-900 font-sans">
<main class="max-w-5xl mx-auto px-6 py-12 space-y-12">
<header>...</header>
<section id="candidates" class="space-y-10">...</section>
<section id="top-recommendation">...</section>
</main>
</body>
</html>
```
## Header
Repo name, date, and a compact legend: solid box = module, dashed line = seam, red arrow = leakage, thick dark box = deep module. No introduction paragraph — straight into the candidates.
## Candidate card
The diagrams carry the weight. Prose is sparse, plain, and uses the glossary terms (from the `/codebase-design` skill) without ceremony.
Each candidate is one `<article>`:
- **Title** — short, names the deepening (e.g. "Collapse the Order intake pipeline").
- **Badge row** — recommendation strength (`Strong` = emerald, `Worth exploring` = amber, `Speculative` = slate), plus a tag for the dependency category (`in-process`, `local-substitutable`, `ports & adapters`, `mock`).
- **Files** — monospaced list, `font-mono text-sm`.
- **Before / After diagram** — the centrepiece. Two columns, side by side. See patterns below.
- **Problem** — one sentence. What hurts.
- **Solution** — one sentence. What changes.
- **Wins** — bullets, ≤6 words each. e.g. "Tests hit one interface", "Pricing logic stops leaking", "Delete 4 shallow wrappers".
- **ADR callout** (if applicable) — one line in an amber-tinted box.
No paragraphs of explanation. If the diagram needs a paragraph to be understood, redraw the diagram.
## Diagram patterns
Pick the pattern that fits the candidate. Mix them. Don't make every diagram look the same — variety is part of the point.
### Mermaid graph (the workhorse for dependencies / call flow)
Use a Mermaid `flowchart` or `graph` when the point is "X calls Y calls Z, and look at the mess." Wrap it in a Tailwind-styled card so it doesn't feel parachuted in. Style with classDef to colour leakage edges red and the deep module dark. Sequence diagrams work well for "before: 6 round-trips; after: 1."
```html
<div class="rounded-lg border border-slate-200 bg-white p-4">
<pre class="mermaid">
flowchart LR
A[OrderHandler] --> B[OrderValidator]
B --> C[OrderRepo]
C -.leak.-> D[PricingClient]
classDef leak stroke:#dc2626,stroke-width:2px;
class C,D leak
</pre>
</div>
```
### Hand-built boxes-and-arrows (when Mermaid's layout fights you)
Modules as `<div>`s with borders and labels. Arrows as inline SVG `<line>` or `<path>` elements positioned absolutely over a relative container. Reach for this when you want the "after" diagram to feel like one thick-bordered deep module with greyed-out internals — Mermaid won't render that with the right weight.
### Cross-section (good for layered shallowness)
Stack horizontal bands (`h-12 border-l-4`) to show layers a call passes through. Before: 6 thin layers each doing nothing. After: 1 thick band labelled with the consolidated responsibility.
### Mass diagram (good for "interface as wide as implementation")
Two rectangles per module — one for interface surface area, one for implementation. Before: interface rectangle is nearly as tall as the implementation rectangle (shallow). After: interface rectangle is short, implementation rectangle is tall (deep).
### Call-graph collapse
Before: a tree of function calls rendered as nested boxes. After: the same tree collapsed into one box, with the now-internal calls shown faded inside it.
## Style guidance
- Lean editorial, not corporate-dashboard. Generous whitespace. Serif optional for headings (`font-serif` works well with stone/slate).
- Colour sparingly: one accent (emerald or indigo) plus red for leakage and amber for warnings.
- Keep diagrams ~320px tall so before/after sits comfortably side by side without scrolling.
- Use `text-xs uppercase tracking-wider` for module labels inside diagrams — they should read as schematic, not as UI.
- The only scripts are the Tailwind CDN and the Mermaid ESM import. The report is otherwise static — no app code, no interactivity beyond Mermaid's own rendering.
## Top recommendation section
One larger card. Candidate name, one sentence on why, anchor link to its card. That's it.
## Tone
Plain English, concise — but the architectural nouns and verbs come straight from the `/codebase-design` skill. Concision is not an excuse to drift.
**Use exactly:** module, interface, implementation, depth, deep, shallow, seam, adapter, leverage, locality.
**Never substitute:** component, service, unit (for module) · API, signature (for interface) · boundary (for seam) · layer, wrapper (for module, when you mean module).
**Phrasings that fit the style:**
- "Order intake module is shallow — interface nearly matches the implementation."
- "Pricing leaks across the seam."
- "Deepen: one interface, one place to test."
- "Two adapters justify the seam: HTTP in prod, in-memory in tests."
**Wins bullets** name the gain in glossary terms: *"locality: bugs concentrate in one module"*, *"leverage: one interface, N call sites"*, *"interface shrinks; implementation absorbs the wrappers"*. Don't write *"easier to maintain"* or *"cleaner code"* — those terms aren't in the glossary and don't earn their place.
No hedging, no throat-clearing, no "it's worth noting that…". If a sentence could be a bullet, make it a bullet. If a bullet could be cut, cut it. If a term isn't in the `/codebase-design` glossary, reach for one that is before inventing a new one.

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---
name: improve-codebase-architecture
description: Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
disable-model-invocation: true
---
# Improve Codebase Architecture
Surface architectural friction and propose **deepening opportunities** — refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.
This command is _informed_ by the project's domain model and built on a shared design vocabulary:
- Run the `/codebase-design` skill for the architecture vocabulary (**module**, **interface**, **depth**, **seam**, **adapter**, **leverage**, **locality**) and its principles (the deletion test, "the interface is the test surface", "one adapter = hypothetical seam, two = real"). Use these terms exactly in every suggestion — don't drift into "component," "service," "API," or "boundary."
- The domain language in `CONTEXT.md` gives names to good seams; ADRs in `docs/adr/` record decisions this command should not re-litigate.
## Process
### 1. Explore
Read the project's domain glossary (`CONTEXT.md`) and any ADRs in the area you're touching first.
Then use the Agent tool with `subagent_type=Explore` to walk the codebase. Don't follow rigid heuristics — explore organically and note where you experience friction:
- Where does understanding one concept require bouncing between many small modules?
- Where are modules **shallow** — interface nearly as complex as the implementation?
- Where have pure functions been extracted just for testability, but the real bugs hide in how they're called (no **locality**)?
- Where do tightly-coupled modules leak across their seams?
- Which parts of the codebase are untested, or hard to test through their current interface?
Apply the **deletion test** to anything you suspect is shallow: would deleting it concentrate complexity, or just move it? A "yes, concentrates" is the signal you want.
### 2. Present candidates as an HTML report
Write a self-contained HTML file to the OS temp directory so nothing lands in the repo. Resolve the temp dir from `$TMPDIR`, falling back to `/tmp` (or `%TEMP%` on Windows), and write to `<tmpdir>/architecture-review-<timestamp>.html` so each run gets a fresh file. Open it for the user — `xdg-open <path>` on Linux, `open <path>` on macOS, `start <path>` on Windows — and tell them the absolute path.
The report uses **Tailwind via CDN** for layout and styling, and **Mermaid via CDN** for diagrams where a graph/flow/sequence reliably communicates the structure. Mix Mermaid with hand-crafted CSS/SVG visuals — use Mermaid when relationships are graph-shaped (call graphs, dependencies, sequences), and hand-built divs/SVG when you want something more editorial (mass diagrams, cross-sections, collapse animations). Each candidate gets a **before/after visualisation**. Be visual.
For each candidate, render a card with:
- **Files** — which files/modules are involved
- **Problem** — why the current architecture is causing friction
- **Solution** — plain English description of what would change
- **Benefits** — explained in terms of locality and leverage, and how tests would improve
- **Before / After diagram** — side-by-side, custom-drawn, illustrating the shallowness and the deepening
- **Recommendation strength** — one of `Strong`, `Worth exploring`, `Speculative`, rendered as a badge
End the report with a **Top recommendation** section: which candidate you'd tackle first and why.
**Use CONTEXT.md vocabulary for the domain, and the `/codebase-design` vocabulary for the architecture.** If `CONTEXT.md` defines "Order," talk about "the Order intake module" — not "the FooBarHandler," and not "the Order service."
**ADR conflicts**: if a candidate contradicts an existing ADR, only surface it when the friction is real enough to warrant revisiting the ADR. Mark it clearly in the card (e.g. a warning callout: _"contradicts ADR-0007 — but worth reopening because…"_). Don't list every theoretical refactor an ADR forbids.
See [HTML-REPORT.md](HTML-REPORT.md) for the full HTML scaffold, diagram patterns, and styling guidance.
Do NOT propose interfaces yet. After the file is written, ask the user: "Which of these would you like to explore?"
### 3. Grilling loop
Once the user picks a candidate, run the `/grilling` skill to walk the design tree with them — constraints, dependencies, the shape of the deepened module, what sits behind the seam, what tests survive.
Side effects happen inline as decisions crystallize — run the `/domain-modeling` skill to keep the domain model current as you go:
- **Naming a deepened module after a concept not in `CONTEXT.md`?** Add the term to `CONTEXT.md`. Create the file lazily if it doesn't exist.
- **Sharpening a fuzzy term during the conversation?** Update `CONTEXT.md` right there.
- **User rejects the candidate with a load-bearing reason?** Offer an ADR, framed as: _"Want me to record this as an ADR so future architecture reviews don't re-suggest it?"_ Only offer when the reason would actually be needed by a future explorer to avoid re-suggesting the same thing — skip ephemeral reasons ("not worth it right now") and self-evident ones.
- **Want to explore alternative interfaces for the deepened module?** Run the `/codebase-design` skill and use its design-it-twice parallel sub-agent pattern.

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---
name: loop-me
description: Grill me about specs for the workflows I want to build, within this workspace.
disable-model-invocation: true
argument-hint: "A workflow to design, or nothing to go find one"
---
Run a stateful `/grilling` session whose only output is **workflow** specs. Use the grilling discipline — relentless, one question at a time, a recommended answer attached to each — aimed at the vocabulary and goal below. Create, edit, and delete specs as the grilling resolves things.
## The loop lens
A **loop** is a recurring pattern in the user's life: their career, their week, their morning, a single repeated activity. Picturing a life as loops within loops reveals how predictable its activities really are — which is what makes them worth **delegating**. Use the lens to find loops worth specifying, and propose ones the user hasn't noticed.
A **workflow** is the spec of one loop, made real. You run a workflow on a loop — the loop is its running instantiation. Workflows live in `workflows/*.md` and are the source of truth.
## Vocabulary
A shared language, reached for only when a workflow calls for it — never a checklist. **Mandate nothing structural**: a workflow needs no AI, no checkpoint, and no schedule unless the grilling shows it does.
- **Trigger** — what fires each run: an **event** (a new email, a new issue) or a **schedule** (every morning). Event-triggering is usually the more efficient.
- **Checkpoint** — a human-in-the-loop point where the user is asked to verify or decide. Some workflows have none and run autonomously; some use no AI at all.
- **Push right** — defer the checkpoint as far as it will go. Do maximal work before involving the human, so they are asked once, late, with everything prepared.
- **Brief** — what a checkpoint presents: a tight, decision-ready summary — what was produced, why, and a link down to the asset itself — never the raw output. The user reads a brief, not a draft. Speed of review is imperative.
## Definition of done
A workflow spec is done when an implementer agent could build it without asking a single question. Grill until then; nothing is done while a question remains.
## The workspace
- `workflows/*.md` — one spec per workflow.
- `NOTES.md` — raw notes on the user's world: the tools they use, the channels they process, and their own terminology for both. When it is empty or thin, interview them about their world before specifying anything. Sharpen fuzzy terms into canonical ones as they surface, and record them here.

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---
name: migrate-to-shoehorn
description: Migrate test files from `as` type assertions to @total-typescript/shoehorn. Use when user mentions shoehorn, wants to replace `as` in tests, or needs partial test data.
---
# Migrate to Shoehorn
## Why shoehorn?
`shoehorn` lets you pass partial data in tests while keeping TypeScript happy. It replaces `as` assertions with type-safe alternatives.
**Test code only.** Never use shoehorn in production code.
Problems with `as` in tests:
- Trained not to use it
- Must manually specify target type
- Double-as (`as unknown as Type`) for intentionally wrong data
## Install
```bash
npm i @total-typescript/shoehorn
```
## Migration patterns
### Large objects with few needed properties
Before:
```ts
type Request = {
body: { id: string };
headers: Record<string, string>;
cookies: Record<string, string>;
// ...20 more properties
};
it("gets user by id", () => {
// Only care about body.id but must fake entire Request
getUser({
body: { id: "123" },
headers: {},
cookies: {},
// ...fake all 20 properties
});
});
```
After:
```ts
import { fromPartial } from "@total-typescript/shoehorn";
it("gets user by id", () => {
getUser(
fromPartial({
body: { id: "123" },
}),
);
});
```
### `as Type``fromPartial()`
Before:
```ts
getUser({ body: { id: "123" } } as Request);
```
After:
```ts
import { fromPartial } from "@total-typescript/shoehorn";
getUser(fromPartial({ body: { id: "123" } }));
```
### `as unknown as Type``fromAny()`
Before:
```ts
getUser({ body: { id: 123 } } as unknown as Request); // wrong type on purpose
```
After:
```ts
import { fromAny } from "@total-typescript/shoehorn";
getUser(fromAny({ body: { id: 123 } }));
```
## When to use each
| Function | Use case |
| --------------- | -------------------------------------------------- |
| `fromPartial()` | Pass partial data that still type-checks |
| `fromAny()` | Pass intentionally wrong data (keeps autocomplete) |
| `fromExact()` | Force full object (swap with fromPartial later) |
## Workflow
1. **Gather requirements** - ask user:
- What test files have `as` assertions causing problems?
- Are they dealing with large objects where only some properties matter?
- Do they need to pass intentionally wrong data for error testing?
2. **Install and migrate**:
- [ ] Install: `npm i @total-typescript/shoehorn`
- [ ] Find test files with `as` assertions: `grep -r " as [A-Z]" --include="*.test.ts" --include="*.spec.ts"`
- [ ] Replace `as Type` with `fromPartial()`
- [ ] Replace `as unknown as Type` with `fromAny()`
- [ ] Add imports from `@total-typescript/shoehorn`
- [ ] Run type check to verify

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---
name: obsidian-vault
description: Search, create, and manage notes in the Obsidian vault with wikilinks and index notes. Use when user wants to find, create, or organize notes in Obsidian.
---
# Obsidian Vault
## Vault location
`/mnt/d/Obsidian Vault/AI Research/`
Mostly flat at root level.
## Naming conventions
- **Index notes**: aggregate related topics (e.g., `Ralph Wiggum Index.md`, `Skills Index.md`, `RAG Index.md`)
- **Title case** for all note names
- No folders for organization - use links and index notes instead
## Linking
- Use Obsidian `[[wikilinks]]` syntax: `[[Note Title]]`
- Notes link to dependencies/related notes at the bottom
- Index notes are just lists of `[[wikilinks]]`
## Workflows
### Search for notes
```bash
# Search by filename
find "/mnt/d/Obsidian Vault/AI Research/" -name "*.md" | grep -i "keyword"
# Search by content
grep -rl "keyword" "/mnt/d/Obsidian Vault/AI Research/" --include="*.md"
```
Or use Grep/Glob tools directly on the vault path.
### Create a new note
1. Use **Title Case** for filename
2. Write content as a unit of learning (per vault rules)
3. Add `[[wikilinks]]` to related notes at the bottom
4. If part of a numbered sequence, use the hierarchical numbering scheme
### Find related notes
Search for `[[Note Title]]` across the vault to find backlinks:
```bash
grep -rl "\\[\\[Note Title\\]\\]" "/mnt/d/Obsidian Vault/AI Research/"
```
### Find index notes
```bash
find "/mnt/d/Obsidian Vault/AI Research/" -name "*Index*"
```

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# Logic Prototype
A tiny interactive terminal app that lets the user drive a state model by hand. Use this when the question is about **business logic, state transitions, or data shape** — the kind of thing that looks reasonable on paper but only feels wrong once you push it through real cases.
## When this is the right shape
- "I'm not sure if this state machine handles the edge case where X then Y."
- "Does this data model actually let me represent the case where..."
- "I want to feel out what the API should look like before writing it."
- Anything where the user wants to **press buttons and watch state change**.
If the question is "what should this look like" — wrong branch. Use [UI.md](UI.md).
## Process
### 1. State the question
Before writing code, write down what state model and what question you're prototyping. One paragraph, in the prototype's README or a comment at the top of the file. A logic prototype that answers the wrong question is pure waste — make the question explicit so it can be checked later, whether the user is watching now or returning to it AFK.
### 2. Pick the language
Use whatever the host project uses. If the project has no obvious runtime (e.g. a docs repo), ask.
Match the project's existing conventions for tooling — don't add a new package manager or runtime just for the prototype.
### 3. Isolate the logic in a portable module
Put the actual logic — the bit that's answering the question — behind a small, pure interface that could be lifted out and dropped into the real codebase later. The TUI around it is throwaway; the logic module shouldn't be.
The right shape depends on the question:
- **A pure reducer**`(state, action) => state`. Good when actions are discrete events and state is a single value.
- **A state machine** — explicit states and transitions. Good when "which actions are even legal right now" is part of the question.
- **A small set of pure functions** over a plain data type. Good when there's no implicit current state — just transformations.
- **A class or module with a clear method surface** when the logic genuinely owns ongoing internal state.
Pick whichever shape best fits the question being asked, *not* whichever is easiest to wire to a TUI. Keep it pure: no I/O, no terminal code, no `console.log` for control flow. The TUI imports it and calls into it; nothing flows the other direction.
This is what makes the prototype useful past its own lifetime. When the question's been answered, the validated reducer / machine / function set can be lifted into the real module — the TUI shell gets deleted.
### 4. Build the smallest TUI that exposes the state
Build it as a **lightweight TUI** — on every tick, clear the screen (`console.clear()` / `print("\033[2J\033[H")` / equivalent) and re-render the whole frame. The user should always see one stable view, not an ever-growing scrollback.
Each frame has two parts, in this order:
1. **Current state**, pretty-printed and diff-friendly (one field per line, or formatted JSON). Use **bold** for field names or section headers and **dim** for less important context (timestamps, IDs, derived values). Native ANSI escape codes are fine — `\x1b[1m` bold, `\x1b[2m` dim, `\x1b[0m` reset. No need to pull in a styling library unless one is already in the project.
2. **Keyboard shortcuts**, listed at the bottom: `[a] add user [d] delete user [t] tick clock [q] quit`. Bold the key, dim the description, or vice-versa — whatever reads cleanly.
Behaviour:
1. **Initialise state** — a single in-memory object/struct. Render the first frame on start.
2. **Read one keystroke (or one line)** at a time, dispatch to a handler that mutates state.
3. **Re-render** the full frame after every action — don't append, replace.
4. **Loop until quit.**
The whole frame should fit on one screen.
### 5. Make it runnable in one command
Add a script to the project's existing task runner (`package.json` scripts, `Makefile`, `justfile`, `pyproject.toml`). The user should run `pnpm run <prototype-name>` or equivalent — never need to remember a path.
If the host project has no task runner, just put the command at the top of the prototype's README.
### 6. Hand it over
Give the user the run command. They'll drive it themselves; the interesting moments are when they say "wait, that shouldn't be possible" or "huh, I assumed X would be different" — those are the bugs in the _idea_, which is the whole point. If they want new actions added, add them. Prototypes evolve.
### 7. Capture the answer
When the prototype has done its job, the answer to the question is the only thing worth keeping. If the user is around, ask what it taught them. If not, leave a `NOTES.md` next to the prototype so the answer can be filled in (or filled in by you, if you've watched the session) before the prototype gets deleted.
## Anti-patterns
- **Don't add tests.** A prototype that needs tests is no longer a prototype.
- **Don't wire it to the real database.** Use an in-memory store unless the question is specifically about persistence.
- **Don't generalise.** No "what if we wanted to support X later." The prototype answers one question.
- **Don't blur the logic and the TUI together.** If the reducer / state machine references `console.log`, prompts, or terminal escape codes, it's no longer portable. Keep the TUI as a thin shell over a pure module.
- **Don't ship the TUI shell into production.** The shell is optimised for being driven by hand from a terminal. The logic module behind it is the bit worth keeping.

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---
name: prototype
description: Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.
---
# Prototype
A prototype is **throwaway code that answers a question**. The question decides the shape.
## Pick a branch
Identify which question is being answered — from the user's prompt, the surrounding code, or by asking if the user is around:
- **"Does this logic / state model feel right?"** → [LOGIC.md](LOGIC.md). Build a tiny interactive terminal app that pushes the state machine through cases that are hard to reason about on paper.
- **"What should this look like?"** → [UI.md](UI.md). Generate several radically different UI variations on a single route, switchable via a URL search param and a floating bottom bar.
The two branches produce very different artifacts — getting this wrong wastes the whole prototype. If the question is genuinely ambiguous and the user isn't reachable, default to whichever branch better matches the surrounding code (a backend module → logic; a page or component → UI) and state the assumption at the top of the prototype.
## Rules that apply to both
1. **Throwaway from day one, and clearly marked as such.** Locate the prototype code close to where it will actually be used (next to the module or page it's prototyping for) so context is obvious — but name it so a casual reader can see it's a prototype, not production. For throwaway UI routes, obey whatever routing convention the project already uses; don't invent a new top-level structure.
2. **One command to run.** Whatever the project's existing task runner supports — `pnpm <name>`, `python <path>`, `bun <path>`, etc. The user must be able to start it without thinking.
3. **No persistence by default.** State lives in memory. Persistence is the thing the prototype is _checking_, not something it should depend on. If the question explicitly involves a database, hit a scratch DB or a local file with a clear "PROTOTYPE — wipe me" name.
4. **Skip the polish.** No tests, no error handling beyond what makes the prototype _runnable_, no abstractions. The point is to learn something fast and then delete it.
5. **Surface the state.** After every action (logic) or on every variant switch (UI), print or render the full relevant state so the user can see what changed.
6. **Delete or absorb when done.** When the prototype has answered its question, either delete it or fold the validated decision into the real code — don't leave it rotting in the repo.
## When done
The _answer_ is the only thing worth keeping from a prototype. Capture it somewhere durable (commit message, ADR, issue, or a `NOTES.md` next to the prototype) along with the question it was answering. If the user is around, that capture is a quick conversation; if not, leave the placeholder so they (or you, on the next pass) can fill in the verdict before deleting the prototype.

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# UI Prototype
Generate **several radically different UI variations** on a single route, switchable from a floating bottom bar. The user flips between variants in the browser, picks one (or steals bits from each), then throws the rest away.
If the question is about logic/state rather than what something looks like — wrong branch. Use [LOGIC.md](LOGIC.md).
## When this is the right shape
- "What should this page look like?"
- "I want to see a few options for this dashboard before committing."
- "Try a different layout for the settings screen."
- Any time the user would otherwise spend a day picking between three vague mockups in their head.
## Two sub-shapes — strongly prefer sub-shape A
A UI prototype is much easier to judge when it's **butting up against the rest of the app** — real header, real sidebar, real data, real density. A throwaway route on its own is a vacuum: every variant looks fine in isolation. Default to sub-shape A whenever there's a plausible existing page to host the variants. Only reach for sub-shape B if the prototype genuinely has no nearby home.
### Sub-shape A — adjustment to an existing page (preferred)
The route already exists. Variants are rendered **on the same route**, gated by a `?variant=` URL search param. The existing data fetching, params, and auth all stay — only the rendering swaps. This is the default; pick it unless there's a specific reason not to.
If the prototype is for something that doesn't yet have a page but *would naturally live inside one* (a new section of the dashboard, a new card on the settings screen, a new step in an existing flow) — that's still sub-shape A. Mount the variants inside the host page.
### Sub-shape B — a new page (last resort)
Only use this when the thing being prototyped genuinely has no existing page to live inside — e.g. an entirely new top-level surface, or a flow that can't be embedded anywhere sensible.
Create a **throwaway route** following whatever routing convention the project already uses — don't invent a new top-level structure. Name it so it's obviously a prototype (e.g. include the word `prototype` in the path or filename). Same `?variant=` pattern.
Before committing to sub-shape B, sanity-check: is there really no existing page this could be embedded in? An empty route hides design problems that a populated one would expose.
In both sub-shapes the floating bottom bar is identical.
## Process
### 1. State the question and pick N
Default to **3 variants**. More than 5 stops being radically different and starts being noise — cap there.
Write down the plan in one line, in the prototype's location or a top-of-file comment:
> "Three variants of the settings page, switchable via `?variant=`, on the existing `/settings` route."
This works whether the user is here to push back or not.
### 2. Generate radically different variants
Draft each variant. Hold each one to:
- The page's purpose and the data it has access to.
- The project's component library / styling system (TailwindCSS, shadcn, MUI, plain CSS, whatever).
- A clear exported component name, e.g. `VariantA`, `VariantB`, `VariantC`.
Variants must be **structurally different** — different layout, different information hierarchy, different primary affordance, not just different colours. Three slightly-tweaked card grids isn't a UI prototype, it's wallpaper. If two drafts come out too similar, redo one with explicit "do not use a card grid" guidance.
### 3. Wire them together
Create a single switcher component on the route:
```tsx
// pseudo-code — adapt to the project's framework
const variant = searchParams.get('variant') ?? 'A';
return (
<>
{variant === 'A' && <VariantA {...data} />}
{variant === 'B' && <VariantB {...data} />}
{variant === 'C' && <VariantC {...data} />}
<PrototypeSwitcher variants={['A','B','C']} current={variant} />
</>
);
```
For sub-shape A (existing page): keep all the existing data fetching above the switcher; only the rendered subtree changes per variant.
For sub-shape B (new page): the throwaway route under `/prototype/<name>` mounts the same switcher.
### 4. Build the floating switcher
A small fixed-position bar at the bottom-centre of the screen with three pieces:
- **Left arrow** — cycles to the previous variant (wraps around).
- **Variant label** — shows the current variant key and, if the variant exports a name, that name too. e.g. `B — Sidebar layout`.
- **Right arrow** — cycles forward (wraps around).
Behaviour:
- Clicking an arrow updates the URL search param (use the framework's router — `router.replace` on Next, `navigate` on React Router, etc) so the variant is shareable and reload-stable.
- Keyboard: `←` and `→` arrow keys also cycle. Don't intercept arrow keys when an `<input>`, `<textarea>`, or `[contenteditable]` is focused.
- Visually distinct from the page (e.g. high-contrast pill, subtle shadow) so it's obviously not part of the design being evaluated.
- Hidden in production builds — gate on `process.env.NODE_ENV !== 'production'` or an equivalent check, so a stray prototype merge can't ship the bar to users.
Put the switcher in a single shared component so both sub-shapes can reuse it. Locate it wherever shared UI lives in the project.
### 5. Hand it over
Surface the URL (and the `?variant=` keys). The user will flip through whenever they get to it. The interesting feedback is usually **"I want the header from B with the sidebar from C"** — that's the actual design they want.
### 6. Capture the answer and clean up
Once a variant has won, write down which one and why (commit message, ADR, issue, or a `NOTES.md` next to the prototype if running AFK and the user hasn't responded yet). Then:
- **Sub-shape A** — delete the losing variants and the switcher; fold the winner into the existing page.
- **Sub-shape B** — promote the winning variant to a real route, delete the throwaway route and the switcher.
Don't leave variant components or the switcher lying around. They rot fast and confuse the next reader.
## Anti-patterns
- **Variants that differ only in colour or copy.** That's a tweak, not a prototype. Real variants disagree about structure.
- **Sharing too much code between variants.** A shared `<Header>` is fine; a shared `<Layout>` defeats the point. Each variant should be free to throw out the layout.
- **Wiring variants to real mutations.** Read-only prototypes are fine. If a variant needs to mutate, point it at a stub — the question is "what should this look like", not "does the backend work".
- **Promoting the prototype directly to production.** The variant code was written under prototype constraints (no tests, minimal error handling). Rewrite it properly when you fold it in.

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---
name: qa
description: Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".
---
# QA Session
Run an interactive QA session. The user describes problems they're encountering. You clarify, explore the codebase for context, and file GitHub issues that are durable, user-focused, and use the project's domain language.
## For each issue the user raises
### 1. Listen and lightly clarify
Let the user describe the problem in their own words. Ask **at most 2-3 short clarifying questions** focused on:
- What they expected vs what actually happened
- Steps to reproduce (if not obvious)
- Whether it's consistent or intermittent
Do NOT over-interview. If the description is clear enough to file, move on.
### 2. Explore the codebase in the background
While talking to the user, kick off an Agent (subagent_type=Explore) in the background to understand the relevant area. The goal is NOT to find a fix — it's to:
- Learn the domain language used in that area (check UBIQUITOUS_LANGUAGE.md)
- Understand what the feature is supposed to do
- Identify the user-facing behavior boundary
This context helps you write a better issue — but the issue itself should NOT reference specific files, line numbers, or internal implementation details.
### 3. Assess scope: single issue or breakdown?
Before filing, decide whether this is a **single issue** or needs to be **broken down** into multiple issues.
Break down when:
- The fix spans multiple independent areas (e.g. "the form validation is wrong AND the success message is missing AND the redirect is broken")
- There are clearly separable concerns that different people could work on in parallel
- The user describes something that has multiple distinct failure modes or symptoms
Keep as a single issue when:
- It's one behavior that's wrong in one place
- The symptoms are all caused by the same root behavior
### 4. File the GitHub issue(s)
Create issues with `gh issue create`. Do NOT ask the user to review first — just file and share URLs.
Issues must be **durable** — they should still make sense after major refactors. Write from the user's perspective.
#### For a single issue
Use this template:
```
## What happened
[Describe the actual behavior the user experienced, in plain language]
## What I expected
[Describe the expected behavior]
## Steps to reproduce
1. [Concrete, numbered steps a developer can follow]
2. [Use domain terms from the codebase, not internal module names]
3. [Include relevant inputs, flags, or configuration]
## Additional context
[Any extra observations from the user or from codebase exploration that help frame the issue — e.g. "this only happens when using the Docker layer, not the filesystem layer" — use domain language but don't cite files]
```
#### For a breakdown (multiple issues)
Create issues in dependency order (blockers first) so you can reference real issue numbers.
Use this template for each sub-issue:
```
## Parent issue
#<parent-issue-number> (if you created a tracking issue) or "Reported during QA session"
## What's wrong
[Describe this specific behavior problem — just this slice, not the whole report]
## What I expected
[Expected behavior for this specific slice]
## Steps to reproduce
1. [Steps specific to THIS issue]
## Blocked by
- #<issue-number> (if this issue can't be fixed until another is resolved)
Or "None — can start immediately" if no blockers.
## Additional context
[Any extra observations relevant to this slice]
```
When creating a breakdown:
- **Prefer many thin issues over few thick ones** — each should be independently fixable and verifiable
- **Mark blocking relationships honestly** — if issue B genuinely can't be tested until issue A is fixed, say so. If they're independent, mark both as "None — can start immediately"
- **Create issues in dependency order** so you can reference real issue numbers in "Blocked by"
- **Maximize parallelism** — the goal is that multiple people (or agents) can grab different issues simultaneously
#### Rules for all issue bodies
- **No file paths or line numbers** — these go stale
- **Use the project's domain language** (check UBIQUITOUS_LANGUAGE.md if it exists)
- **Describe behaviors, not code** — "the sync service fails to apply the patch" not "applyPatch() throws on line 42"
- **Reproduction steps are mandatory** — if you can't determine them, ask the user
- **Keep it concise** — a developer should be able to read the issue in 30 seconds
After filing, print all issue URLs (with blocking relationships summarized) and ask: "Next issue, or are we done?"
### 5. Continue the session
Keep going until the user says they're done. Each issue is independent — don't batch them.

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---
name: request-refactor-plan
description: Create a detailed refactor plan with tiny commits via user interview, then file it as a GitHub issue. Use when user wants to plan a refactor, create a refactoring RFC, or break a refactor into safe incremental steps.
---
This skill will be invoked when the user wants to create a refactor request. You should go through the steps below. You may skip steps if you don't consider them necessary.
1. Ask the user for a long, detailed description of the problem they want to solve and any potential ideas for solutions.
2. Explore the repo to verify their assertions and understand the current state of the codebase.
3. Ask whether they have considered other options, and present other options to them.
4. Interview the user about the implementation. Be extremely detailed and thorough.
5. Hammer out the exact scope of the implementation. Work out what you plan to change and what you plan not to change.
6. Look in the codebase to check for test coverage of this area of the codebase. If there is insufficient test coverage, ask the user what their plans for testing are.
7. Break the implementation into a plan of tiny commits. Remember Martin Fowler's advice to "make each refactoring step as small as possible, so that you can always see the program working."
8. Create a GitHub issue with the refactor plan. Use the following template for the issue description:
<refactor-plan-template>
## Problem Statement
The problem that the developer is facing, from the developer's perspective.
## Solution
The solution to the problem, from the developer's perspective.
## Commits
A LONG, detailed implementation plan. Write the plan in plain English, breaking down the implementation into the tiniest commits possible. Each commit should leave the codebase in a working state.
## Decision Document
A list of implementation decisions that were made. This can include:
- The modules that will be built/modified
- The interfaces of those modules that will be modified
- Technical clarifications from the developer
- Architectural decisions
- Schema changes
- API contracts
- Specific interactions
Do NOT include specific file paths or code snippets. They may end up being outdated very quickly.
## Testing Decisions
A list of testing decisions that were made. Include:
- A description of what makes a good test (only test external behavior, not implementation details)
- Which modules will be tested
- Prior art for the tests (i.e. similar types of tests in the codebase)
## Out of Scope
A description of the things that are out of scope for this refactor.
## Further Notes (optional)
Any further notes about the refactor.
</refactor-plan-template>

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---
name: research
description: Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
---
Spin up a **background agent** to do the research, so you keep working while it reads.
Its job:
1. Investigate the question against **primary sources** — official docs, source code, specs, first-party APIs — not a secondary write-up of them. Follow every claim back to the source that owns it.
2. Write the findings to a single Markdown file, citing each claim's source.
3. Save it where the repo already keeps such notes; match the existing convention, and if there is none, put it somewhere sensible and say where.

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---
name: resolving-merge-conflicts
description: "Use when you need to resolve an in-progress git merge/rebase conflict."
---
1. **See the current state** of the merge/rebase. Check git history, and the conflicting files.
2. **Find the primary sources** for each conflict. Understand deeply why each change was made, and what the original intent was. Read the commit messages, check the PRs, check original issues/tickets.
3. **Resolve each hunk.** Preserve both intents where possible. Where incompatible, pick the one matching the merge's stated goal and note the trade-off. Do **not** invent new behaviour. Always resolve; never `--abort`.
4. Discover the project's **automated checks** and run them — typically typecheck, then tests, then format. Fix anything the merge broke.
5. **Finish the merge/rebase.** Stage everything and commit. If rebasing, continue the rebase process until all commits are rebased.

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---
name: review
description: Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
---
Two-axis review of the diff between `HEAD` and a fixed point the user supplies:
- **Standards** — does the code conform to this repo's documented coding standards?
- **Spec** — does the code faithfully implement the originating issue / PRD / spec?
Both axes run as **parallel sub-agents** so they don't pollute each other's context, then this skill aggregates their findings.
The issue tracker should have been provided to you — run `/setup-matt-pocock-skills` if `docs/agents/issue-tracker.md` is missing.
## Process
### 1. Pin the fixed point
Whatever the user said is the fixed point — a commit SHA, branch name, tag, `main`, `HEAD~5`, etc. If they didn't specify one, ask for it.
Capture the diff command once: `git diff <fixed-point>...HEAD` (three-dot, so the comparison is against the merge-base). Also note the list of commits via `git log <fixed-point>..HEAD --oneline`.
Before going further, confirm the fixed point resolves (`git rev-parse <fixed-point>`) and the diff is non-empty. A bad ref or empty diff should fail here — not inside two parallel sub-agents.
### 2. Identify the spec source
Look for the originating spec, in this order:
1. Issue references in the commit messages (`#123`, `Closes #45`, GitLab `!67`, etc.) — fetch via the workflow in `docs/agents/issue-tracker.md`.
2. A path the user passed as an argument.
3. A PRD/spec file under `docs/`, `specs/`, or `.scratch/` matching the branch name or feature.
4. If nothing is found, ask the user where the spec is. If they say there isn't one, the **Spec** sub-agent will skip and report "no spec available".
### 3. Identify the standards sources
Anything in the repo that documents how code should be written, such as `CODING_STANDARDS.md` or `CONTRIBUTING.md`.
### 4. Spawn both sub-agents in parallel
Send a single message with two `Agent` tool calls. Use the `general-purpose` subagent for both.
**Standards sub-agent prompt** — include:
- The full diff command and commit list.
- The list of standards-source files you found in step 3.
- The brief: "Report — per file/hunk where relevant — every place the diff violates a documented standard. Cite the standard (file + the rule). Distinguish hard violations from judgement calls. Skip anything tooling enforces. Under 400 words."
**Spec sub-agent prompt** — include:
- The diff command and commit list.
- The path or fetched contents of the spec.
- The brief: "Report: (a) requirements the spec asked for that are missing or partial; (b) behaviour in the diff that wasn't asked for (scope creep); (c) requirements that look implemented but where the implementation looks wrong. Quote the spec line for each finding. Under 400 words."
If the spec is missing, skip the Spec sub-agent and note this in the final report.
### 5. Aggregate
Present the two reports under `## Standards` and `## Spec` headings, verbatim or lightly cleaned. Do **not** merge or rerank findings — the two axes are deliberately separate (see _Why two axes_).
End with a one-line summary: total findings per axis, and the worst issue _within each axis_ (if any). Don't pick a single winner across axes — that's the reranking the separation exists to prevent.
## Why two axes
A change can pass one axis and fail the other:
- Code that follows every standard but implements the wrong thing → **Standards pass, Spec fail.**
- Code that does exactly what the issue asked but breaks the project's conventions → **Spec pass, Standards fail.**
Reporting them separately stops one axis from masking the other.

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---
name: scaffold-exercises
description: Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.
---
# Scaffold Exercises
Create exercise directory structures that pass `pnpm ai-hero-cli internal lint`, then commit with `git commit`.
## Directory naming
- **Sections**: `XX-section-name/` inside `exercises/` (e.g., `01-retrieval-skill-building`)
- **Exercises**: `XX.YY-exercise-name/` inside a section (e.g., `01.03-retrieval-with-bm25`)
- Section number = `XX`, exercise number = `XX.YY`
- Names are dash-case (lowercase, hyphens)
## Exercise variants
Each exercise needs at least one of these subfolders:
- `problem/` - student workspace with TODOs
- `solution/` - reference implementation
- `explainer/` - conceptual material, no TODOs
When stubbing, default to `explainer/` unless the plan specifies otherwise.
## Required files
Each subfolder (`problem/`, `solution/`, `explainer/`) needs a `readme.md` that:
- Is **not empty** (must have real content, even a single title line works)
- Has no broken links
When stubbing, create a minimal readme with a title and a description:
```md
# Exercise Title
Description here
```
If the subfolder has code, it also needs a `main.ts` (>1 line). But for stubs, a readme-only exercise is fine.
## Workflow
1. **Parse the plan** - extract section names, exercise names, and variant types
2. **Create directories** - `mkdir -p` for each path
3. **Create stub readmes** - one `readme.md` per variant folder with a title
4. **Run lint** - `pnpm ai-hero-cli internal lint` to validate
5. **Fix any errors** - iterate until lint passes
## Lint rules summary
The linter (`pnpm ai-hero-cli internal lint`) checks:
- Each exercise has subfolders (`problem/`, `solution/`, `explainer/`)
- At least one of `problem/`, `explainer/`, or `explainer.1/` exists
- `readme.md` exists and is non-empty in the primary subfolder
- No `.gitkeep` files
- No `speaker-notes.md` files
- No broken links in readmes
- No `pnpm run exercise` commands in readmes
- `main.ts` required per subfolder unless it's readme-only
## Moving/renaming exercises
When renumbering or moving exercises:
1. Use `git mv` (not `mv`) to rename directories - preserves git history
2. Update the numeric prefix to maintain order
3. Re-run lint after moves
Example:
```bash
git mv exercises/01-retrieval/01.03-embeddings exercises/01-retrieval/01.04-embeddings
```
## Example: stubbing from a plan
Given a plan like:
```
Section 05: Memory Skill Building
- 05.01 Introduction to Memory
- 05.02 Short-term Memory (explainer + problem + solution)
- 05.03 Long-term Memory
```
Create:
```bash
mkdir -p exercises/05-memory-skill-building/05.01-introduction-to-memory/explainer
mkdir -p exercises/05-memory-skill-building/05.02-short-term-memory/{explainer,problem,solution}
mkdir -p exercises/05-memory-skill-building/05.03-long-term-memory/explainer
```
Then create readme stubs:
```
exercises/05-memory-skill-building/05.01-introduction-to-memory/explainer/readme.md -> "# Introduction to Memory"
exercises/05-memory-skill-building/05.02-short-term-memory/explainer/readme.md -> "# Short-term Memory"
exercises/05-memory-skill-building/05.02-short-term-memory/problem/readme.md -> "# Short-term Memory"
exercises/05-memory-skill-building/05.02-short-term-memory/solution/readme.md -> "# Short-term Memory"
exercises/05-memory-skill-building/05.03-long-term-memory/explainer/readme.md -> "# Long-term Memory"
```

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---
name: setup-matt-pocock-skills
description: Configure this repo for the engineering skills — set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.
disable-model-invocation: true
---
# Setup Matt Pocock's Skills
Scaffold the per-repo configuration that the engineering skills assume:
- **Issue tracker** — where issues live (GitHub by default; local markdown is also supported out of the box)
- **Triage labels** — the strings used for the five canonical triage roles
- **Domain docs** — where `CONTEXT.md` and ADRs live, and the consumer rules for reading them
This is a prompt-driven skill, not a deterministic script. Explore, present what you found, confirm with the user, then write.
## Process
### 1. Explore
Look at the current repo to understand its starting state. Read whatever exists; don't assume:
- `git remote -v` and `.git/config` — is this a GitHub repo? Which one?
- `AGENTS.md` and `CLAUDE.md` at the repo root — does either exist? Is there already an `## Agent skills` section in either?
- `CONTEXT.md` and `CONTEXT-MAP.md` at the repo root
- `docs/adr/` and any `src/*/docs/adr/` directories
- `docs/agents/` — does this skill's prior output already exist?
- `.scratch/` — sign that a local-markdown issue tracker convention is already in use
### 2. Present findings and ask
Summarise what's present and what's missing. Then walk the user through the three decisions **one at a time** — present a section, get the user's answer, then move to the next. Don't dump all three at once.
Assume the user does not know what these terms mean. Each section starts with a short explainer (what it is, why these skills need it, what changes if they pick differently). Then show the choices and the default.
**Section A — Issue tracker.**
> Explainer: The "issue tracker" is where issues live for this repo. Skills like `to-tickets`, `triage`, `to-spec`, and `qa` read from and write to it — they need to know whether to call `gh issue create`, write a markdown file under `.scratch/`, or follow some other workflow you describe. Pick the place you actually track work for this repo.
Default posture: these skills were designed for GitHub. If a `git remote` points at GitHub, propose that. If a `git remote` points at GitLab (`gitlab.com` or a self-hosted host), propose GitLab. Otherwise (or if the user prefers), offer:
- **GitHub** — issues live in the repo's GitHub Issues (uses the `gh` CLI)
- **GitLab** — issues live in the repo's GitLab Issues (uses the [`glab`](https://gitlab.com/gitlab-org/cli) CLI)
- **Local markdown** — issues live as files under `.scratch/<feature>/` in this repo (good for solo projects or repos without a remote)
- **Other** (Jira, Linear, etc.) — ask the user to describe the workflow in one paragraph; the skill will record it as freeform prose
If — and only if — the user picked **GitHub** or **GitLab**, ask one follow-up:
> Explainer: Open-source repos often receive feature requests as pull requests, not just issues — a PR is an issue with attached code. If you turn this on, `/triage` pulls *external* PRs into the same queue and runs them through the same labels and states as issues (collaborators' in-flight PRs are left alone). Leave it off if PRs aren't a request surface for you.
- **PRs as a request surface** — yes / no (default: no). Record the answer in `docs/agents/issue-tracker.md`. For local-markdown and other trackers, skip this question — there are no PRs.
**Section B — Triage label vocabulary.**
> Explainer: When the `triage` skill processes an incoming issue, it moves it through a state machine — needs evaluation, waiting on reporter, ready for an AFK agent to pick up, ready for a human, or won't fix. To do that, it needs to apply labels (or the equivalent in your issue tracker) that match strings *you've actually configured*. If your repo already uses different label names (e.g. `bug:triage` instead of `needs-triage`), map them here so the skill applies the right ones instead of creating duplicates.
The five canonical roles:
- `needs-triage` — maintainer needs to evaluate
- `needs-info` — waiting on reporter
- `ready-for-agent` — fully specified, AFK-ready (an agent can pick it up with no human context)
- `ready-for-human` — needs human implementation
- `wontfix` — will not be actioned
Default: each role's string equals its name. Ask the user if they want to override any. If their issue tracker has no existing labels, the defaults are fine.
**Section C — Domain docs.**
> Explainer: Some skills (`improve-codebase-architecture`, `diagnosing-bugs`, `tdd`) read a `CONTEXT.md` file to learn the project's domain language, and `docs/adr/` for past architectural decisions. They need to know whether the repo has one global context or multiple (e.g. a monorepo with separate frontend/backend contexts) so they look in the right place.
Confirm the layout:
- **Single-context** — one `CONTEXT.md` + `docs/adr/` at the repo root. Most repos are this.
- **Multi-context**`CONTEXT-MAP.md` at the root pointing to per-context `CONTEXT.md` files (typically a monorepo).
### 3. Confirm and edit
Show the user a draft of:
- The `## Agent skills` block to add to whichever of `CLAUDE.md` / `AGENTS.md` is being edited (see step 4 for selection rules)
- The contents of `docs/agents/issue-tracker.md`, `docs/agents/triage-labels.md`, `docs/agents/domain.md`
Let them edit before writing.
### 4. Write
**Pick the file to edit:**
- If `CLAUDE.md` exists, edit it.
- Else if `AGENTS.md` exists, edit it.
- If neither exists, ask the user which one to create — don't pick for them.
Never create `AGENTS.md` when `CLAUDE.md` already exists (or vice versa) — always edit the one that's already there.
If an `## Agent skills` block already exists in the chosen file, update its contents in-place rather than appending a duplicate. Don't overwrite user edits to the surrounding sections.
The block:
```markdown
## Agent skills
### Issue tracker
[one-line summary of where issues are tracked, plus whether external PRs are a triage surface]. See `docs/agents/issue-tracker.md`.
### Triage labels
[one-line summary of the label vocabulary]. See `docs/agents/triage-labels.md`.
### Domain docs
[one-line summary of layout — "single-context" or "multi-context"]. See `docs/agents/domain.md`.
```
Then write the three docs files using the seed templates in this skill folder as a starting point:
- [issue-tracker-github.md](./issue-tracker-github.md) — GitHub issue tracker
- [issue-tracker-gitlab.md](./issue-tracker-gitlab.md) — GitLab issue tracker
- [issue-tracker-local.md](./issue-tracker-local.md) — local-markdown issue tracker
- [triage-labels.md](./triage-labels.md) — label mapping
- [domain.md](./domain.md) — domain doc consumer rules + layout
For "other" issue trackers, write `docs/agents/issue-tracker.md` from scratch using the user's description.
### 5. Done
Tell the user the setup is complete and which engineering skills will now read from these files. Mention they can edit `docs/agents/*.md` directly later — re-running this skill is only necessary if they want to switch issue trackers or restart from scratch.

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# Domain Docs
How the engineering skills should consume this repo's domain documentation when exploring the codebase.
## Before exploring, read these
- **`CONTEXT.md`** at the repo root, or
- **`CONTEXT-MAP.md`** at the repo root if it exists — it points at one `CONTEXT.md` per context. Read each one relevant to the topic.
- **`docs/adr/`** — read ADRs that touch the area you're about to work in. In multi-context repos, also check `src/<context>/docs/adr/` for context-scoped decisions.
If any of these files don't exist, **proceed silently**. Don't flag their absence; don't suggest creating them upfront. The `/domain-modeling` skill (reached via `/grill-with-docs` and `/improve-codebase-architecture`) creates them lazily when terms or decisions actually get resolved.
## File structure
Single-context repo (most repos):
```
/
├── CONTEXT.md
├── docs/adr/
│ ├── 0001-event-sourced-orders.md
│ └── 0002-postgres-for-write-model.md
└── src/
```
Multi-context repo (presence of `CONTEXT-MAP.md` at the root):
```
/
├── CONTEXT-MAP.md
├── docs/adr/ ← system-wide decisions
└── src/
├── ordering/
│ ├── CONTEXT.md
│ └── docs/adr/ ← context-specific decisions
└── billing/
├── CONTEXT.md
└── docs/adr/
```
## Use the glossary's vocabulary
When your output names a domain concept (in an issue title, a refactor proposal, a hypothesis, a test name), use the term as defined in `CONTEXT.md`. Don't drift to synonyms the glossary explicitly avoids.
If the concept you need isn't in the glossary yet, that's a signal — either you're inventing language the project doesn't use (reconsider) or there's a real gap (note it for `/domain-modeling`).
## Flag ADR conflicts
If your output contradicts an existing ADR, surface it explicitly rather than silently overriding:
> _Contradicts ADR-0007 (event-sourced orders) — but worth reopening because…_

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# Issue tracker: GitHub
Issues and PRDs for this repo live as GitHub issues. Use the `gh` CLI for all operations.
## Conventions
- **Create an issue**: `gh issue create --title "..." --body "..."`. Use a heredoc for multi-line bodies.
- **Read an issue**: `gh issue view <number> --comments`, filtering comments by `jq` and also fetching labels.
- **List issues**: `gh issue list --state open --json number,title,body,labels,comments --jq '[.[] | {number, title, body, labels: [.labels[].name], comments: [.comments[].body]}]'` with appropriate `--label` and `--state` filters.
- **Comment on an issue**: `gh issue comment <number> --body "..."`
- **Apply / remove labels**: `gh issue edit <number> --add-label "..."` / `--remove-label "..."`
- **Close**: `gh issue close <number> --comment "..."`
Infer the repo from `git remote -v``gh` does this automatically when run inside a clone.
## Pull requests as a triage surface
**PRs as a request surface: no.** _(Set to `yes` if this repo treats external PRs as feature requests; `/triage` reads this flag.)_
When set to `yes`, PRs run through the same labels and states as issues, using the `gh pr` equivalents:
- **Read a PR**: `gh pr view <number> --comments` and `gh pr diff <number>` for the diff.
- **List external PRs for triage**: `gh pr list --state open --json number,title,body,labels,author,authorAssociation,comments` then keep only `authorAssociation` of `CONTRIBUTOR`, `FIRST_TIME_CONTRIBUTOR`, or `NONE` (drop `OWNER`/`MEMBER`/`COLLABORATOR`).
- **Comment / label / close**: `gh pr comment`, `gh pr edit --add-label`/`--remove-label`, `gh pr close`.
GitHub shares one number space across issues and PRs, so a bare `#42` may be either — resolve with `gh pr view 42` and fall back to `gh issue view 42`.
## When a skill says "publish to the issue tracker"
Create a GitHub issue.
## When a skill says "fetch the relevant ticket"
Run `gh issue view <number> --comments`.
## Wayfinding operations
Used by `/wayfinder`. The **map** is a single issue with **child** issues as tickets.
- **Map**: a single issue labelled `wayfinder:map`, holding the Notes / Decisions-so-far / Fog body. `gh issue create --label wayfinder:map`.
- **Child ticket**: an issue linked to the map as a GitHub sub-issue (`gh api` on the sub-issues endpoint). Where sub-issues aren't enabled, add the child to a task list in the map body and put `Part of #<map>` at the top of the child body. Labels: `wayfinder:<type>` (`research`/`prototype`/`grilling`/`task`). Once claimed, the ticket is assigned to the driving dev.
- **Blocking**: GitHub's **native issue dependencies** — the canonical, UI-visible representation. Add an edge with `gh api --method POST repos/<owner>/<repo>/issues/<child>/dependencies/blocked_by -F issue_id=<blocker-db-id>`, where `<blocker-db-id>` is the blocker's numeric **database id** (`gh api repos/<owner>/<repo>/issues/<n> --jq .id`, _not_ the `#number` or `node_id`). GitHub reports `issue_dependencies_summary.blocked_by` (open blockers only — the live gate). Where dependencies aren't available, fall back to a `Blocked by: #<n>, #<n>` line at the top of the child body. A ticket is unblocked when every blocker is closed.
- **Frontier query**: list the map's open children (`gh issue list --state open`, scoped to the map's sub-issues / task list), drop any with an open blocker (`issue_dependencies_summary.blocked_by > 0`, or an open issue in the `Blocked by` line) or an assignee; first in map order wins.
- **Claim**: `gh issue edit <n> --add-assignee @me` — the session's first write.
- **Resolve**: `gh issue comment <n> --body "<answer>"`, then `gh issue close <n>`, then append a context pointer (gist + link) to the map's Decisions-so-far.

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# Issue tracker: GitLab
Issues and PRDs for this repo live as GitLab issues. Use the [`glab`](https://gitlab.com/gitlab-org/cli) CLI for all operations.
## Conventions
- **Create an issue**: `glab issue create --title "..." --description "..."`. Use a heredoc for multi-line descriptions. Pass `--description -` to open an editor.
- **Read an issue**: `glab issue view <number> --comments`. Use `-F json` for machine-readable output.
- **List issues**: `glab issue list -F json` with appropriate `--label` filters.
- **Comment on an issue**: `glab issue note <number> --message "..."`. GitLab calls comments "notes".
- **Apply / remove labels**: `glab issue update <number> --label "..."` / `--unlabel "..."`. Multiple labels can be comma-separated or by repeating the flag.
- **Close**: `glab issue close <number>`. `glab issue close` does not accept a closing comment, so post the explanation first with `glab issue note <number> --message "..."`, then close.
- **Merge requests**: GitLab calls PRs "merge requests". Use `glab mr create`, `glab mr view`, `glab mr note`, etc. — the same shape as `gh pr ...` with `mr` in place of `pr` and `note`/`--message` in place of `comment`/`--body`.
Infer the repo from `git remote -v``glab` does this automatically when run inside a clone.
## Merge requests as a triage surface
**MRs as a request surface: no.** _(Set to `yes` if this repo treats external merge requests as feature requests; `/triage` reads this flag.)_
When set to `yes`, MRs run through the same labels and states as issues, using the `glab mr` equivalents:
- **Read an MR**: `glab mr view <number> --comments` and `glab mr diff <number>` for the diff.
- **List external MRs for triage**: `glab mr list -F json`, then keep only MRs whose author is not a project member/owner (a contributor's MR, not a maintainer's in-flight work).
- **Comment / label / close**: `glab mr note`, `glab mr update --label`/`--unlabel`, `glab mr close`.
Unlike GitHub, GitLab numbers issues and MRs separately, so `#42` is unambiguous once you know which surface the maintainer means.
## When a skill says "publish to the issue tracker"
Create a GitLab issue.
## When a skill says "fetch the relevant ticket"
Run `glab issue view <number> --comments`.
## Wayfinding operations
Used by `/wayfinder`. The **map** is a single issue with **child** issues as tickets.
- **Map**: a single issue labelled `wayfinder:map`, holding the Notes / Decisions-so-far / Fog body. `glab issue create --label wayfinder:map`. (On GitLab tiers with native epics, an epic may hold the map instead; a labelled issue works everywhere.)
- **Child ticket**: an issue carrying `Part of #<map>` at the top of its description and labels `wayfinder:<type>` (`research`/`prototype`/`grilling`/`task`). Once claimed, the ticket is assigned to the driving dev.
- **Blocking**: GitLab's **native blocking link** — the canonical, UI-visible representation. Add it with the `/blocked_by #<n>` quick action, posted as a note (`glab issue note <child> --message "/blocked_by #<blocker>"`). Native blocking links are a Premium/Ultimate feature; on the free tier (or where unavailable) fall back to a `Blocked by: #<n>, #<n>` line at the top of the description. A ticket is unblocked when every blocker is closed.
- **Frontier query**: `glab issue list -F json` scoped to the map's children, drop any with an open blocker — a native `blocked_by` link to an open issue (`glab api projects/:id/issues/:iid/links`), or an open issue in the `Blocked by` line — or an assignee; first in map order wins.
- **Claim**: `glab issue update <n> --assignee @me` — the session's first write.
- **Resolve**: `glab issue note <n> --message "<answer>"`, then `glab issue close <n>`, then append a context pointer (gist + link) to the map's Decisions-so-far.

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# Issue tracker: Local Markdown
Issues and PRDs for this repo live as markdown files in `.scratch/`.
## Conventions
- One feature per directory: `.scratch/<feature-slug>/`
- The PRD is `.scratch/<feature-slug>/PRD.md`
- Implementation issues are `.scratch/<feature-slug>/issues/<NN>-<slug>.md`, numbered from `01`
- Triage state is recorded as a `Status:` line near the top of each issue file (see `triage-labels.md` for the role strings)
- Comments and conversation history append to the bottom of the file under a `## Comments` heading
## When a skill says "publish to the issue tracker"
Create a new file under `.scratch/<feature-slug>/` (creating the directory if needed).
## When a skill says "fetch the relevant ticket"
Read the file at the referenced path. The user will normally pass the path or the issue number directly.
## Wayfinding operations
Used by `/wayfinder`. The **map** is a file with one **child** file per ticket.
- **Map**: `.scratch/<effort>/map.md` — the Notes / Decisions-so-far / Fog body.
- **Child ticket**: `.scratch/<effort>/issues/NN-<slug>.md`, numbered from `01`, with the question in the body. A `Type:` line records the ticket type (`research`/`prototype`/`grilling`/`task`); a `Status:` line records `claimed`/`resolved`.
- **Blocking**: a `Blocked by: NN, NN` line near the top. A ticket is unblocked when every file it lists is `resolved`.
- **Frontier**: scan `.scratch/<effort>/issues/` for files that are open, unblocked, and unclaimed; first by number wins.
- **Claim**: set `Status: claimed` and save before any work.
- **Resolve**: append the answer under an `## Answer` heading, set `Status: resolved`, then append a context pointer (gist + link) to the map's Decisions-so-far in `map.md`.

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# Triage Labels
The skills speak in terms of five canonical triage roles. This file maps those roles to the actual label strings used in this repo's issue tracker.
| Label in mattpocock/skills | Label in our tracker | Meaning |
| -------------------------- | -------------------- | ---------------------------------------- |
| `needs-triage` | `needs-triage` | Maintainer needs to evaluate this issue |
| `needs-info` | `needs-info` | Waiting on reporter for more information |
| `ready-for-agent` | `ready-for-agent` | Fully specified, ready for an AFK agent |
| `ready-for-human` | `ready-for-human` | Requires human implementation |
| `wontfix` | `wontfix` | Will not be actioned |
When a skill mentions a role (e.g. "apply the AFK-ready triage label"), use the corresponding label string from this table.
Edit the right-hand column to match whatever vocabulary you actually use.

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---
name: setup-pre-commit
description: Set up Husky pre-commit hooks with lint-staged (Prettier), type checking, and tests in the current repo. Use when user wants to add pre-commit hooks, set up Husky, configure lint-staged, or add commit-time formatting/typechecking/testing.
---
# Setup Pre-Commit Hooks
## What This Sets Up
- **Husky** pre-commit hook
- **lint-staged** running Prettier on all staged files
- **Prettier** config (if missing)
- **typecheck** and **test** scripts in the pre-commit hook
## Steps
### 1. Detect package manager
Check for `package-lock.json` (npm), `pnpm-lock.yaml` (pnpm), `yarn.lock` (yarn), `bun.lockb` (bun). Use whichever is present. Default to npm if unclear.
### 2. Install dependencies
Install as devDependencies:
```
husky lint-staged prettier
```
### 3. Initialize Husky
```bash
npx husky init
```
This creates `.husky/` dir and adds `prepare: "husky"` to package.json.
### 4. Create `.husky/pre-commit`
Write this file (no shebang needed for Husky v9+):
```
npx lint-staged
npm run typecheck
npm run test
```
**Adapt**: Replace `npm` with detected package manager. If repo has no `typecheck` or `test` script in package.json, omit those lines and tell the user.
### 5. Create `.lintstagedrc`
```json
{
"*": "prettier --ignore-unknown --write"
}
```
### 6. Create `.prettierrc` (if missing)
Only create if no Prettier config exists. Use these defaults:
```json
{
"useTabs": false,
"tabWidth": 2,
"printWidth": 80,
"singleQuote": false,
"trailingComma": "es5",
"semi": true,
"arrowParens": "always"
}
```
### 7. Verify
- [ ] `.husky/pre-commit` exists and is executable
- [ ] `.lintstagedrc` exists
- [ ] `prepare` script in package.json is `"husky"`
- [ ] `prettier` config exists
- [ ] Run `npx lint-staged` to verify it works
### 8. Commit
Stage all changed/created files and commit with message: `Add pre-commit hooks (husky + lint-staged + prettier)`
This will run through the new pre-commit hooks — a good smoke test that everything works.
## Notes
- Husky v9+ doesn't need shebangs in hook files
- `prettier --ignore-unknown` skips files Prettier can't parse (images, etc.)
- The pre-commit runs lint-staged first (fast, staged-only), then full typecheck and tests

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---
name: tdd
description: Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
---
# Test-Driven Development
TDD is the red → green loop. This skill is the reference that makes that loop produce tests worth keeping: what a good test is, where tests go, the anti-patterns, and the rules of the loop. Every section applies on every cycle — consult them before and during the loop, not after.
When exploring the codebase, read `CONTEXT.md` (if it exists) so test names and interface vocabulary match the project's domain language, and respect ADRs in the area you're touching.
## What a good test is
Tests verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't. A good test reads like a specification — "user can checkout with valid cart" tells you exactly what capability exists — and survives refactors because it doesn't care about internal structure.
See [tests.md](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines.
## Seams — where tests go
A **seam** is the public boundary you test at: the interface where you observe behavior without reaching inside. Tests live at seams, never against internals.
**Test only at pre-agreed seams.** Before writing any test, write down the seams under test and confirm them with the user. No test is written at an unconfirmed seam. You can't test everything — agreeing the seams up front is how testing effort lands on the critical paths and complex logic instead of every edge case.
Ask: "What's the public interface, and which seams should we test?"
## Anti-patterns
- **Implementation-coupled** — mocks internal collaborators, tests private methods, or verifies through a side channel (querying the database instead of using the interface). The tell: the test breaks when you refactor but behavior hasn't changed.
- **Tautological** — the assertion recomputes the expected value the way the code does (`expect(add(a, b)).toBe(a + b)`, a snapshot derived by hand the same way, a constant asserted equal to itself), so it passes by construction and can never disagree with the code. Expected values must come from an independent source of truth — a known-good literal, a worked example, the spec.
- **Horizontal slicing** — writing all tests first, then all implementation. Bulk tests verify _imagined_ behavior: you test the _shape_ of things rather than user-facing behavior, the tests go insensitive to real changes, and you commit to test structure before understanding the implementation. Work in **vertical slices** instead — one test → one implementation → repeat, each test a **tracer bullet** that responds to what the last cycle taught you.
## Rules of the loop
- **Red before green.** Write the failing test first, then only enough code to pass it. Don't anticipate future tests or add speculative features.
- **One slice at a time.** One seam, one test, one minimal implementation per cycle.
- **Refactoring is not part of the loop.** It belongs to the review stage (see the `code-review` skill), not the red → green implementation cycle.

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# When to Mock
Mock at **system boundaries** only:
- External APIs (payment, email, etc.)
- Databases (sometimes - prefer test DB)
- Time/randomness
- File system (sometimes)
Don't mock:
- Your own classes/modules
- Internal collaborators
- Anything you control
## Designing for Mockability
At system boundaries, design interfaces that are easy to mock:
**1. Use dependency injection**
Pass external dependencies in rather than creating them internally:
```typescript
// Easy to mock
function processPayment(order, paymentClient) {
return paymentClient.charge(order.total);
}
// Hard to mock
function processPayment(order) {
const client = new StripeClient(process.env.STRIPE_KEY);
return client.charge(order.total);
}
```
**2. Prefer SDK-style interfaces over generic fetchers**
Create specific functions for each external operation instead of one generic function with conditional logic:
```typescript
// GOOD: Each function is independently mockable
const api = {
getUser: (id) => fetch(`/users/${id}`),
getOrders: (userId) => fetch(`/users/${userId}/orders`),
createOrder: (data) => fetch('/orders', { method: 'POST', body: data }),
};
// BAD: Mocking requires conditional logic inside the mock
const api = {
fetch: (endpoint, options) => fetch(endpoint, options),
};
```
The SDK approach means:
- Each mock returns one specific shape
- No conditional logic in test setup
- Easier to see which endpoints a test exercises
- Type safety per endpoint

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# Good and Bad Tests
## Good Tests
**Integration-style**: Test through real interfaces, not mocks of internal parts.
```typescript
// GOOD: Tests observable behavior
test("user can checkout with valid cart", async () => {
const cart = createCart();
cart.add(product);
const result = await checkout(cart, paymentMethod);
expect(result.status).toBe("confirmed");
});
```
Characteristics:
- Tests behavior users/callers care about
- Uses public API only
- Survives internal refactors
- Describes WHAT, not HOW
- One logical assertion per test
## Bad Tests
**Implementation-detail tests**: Coupled to internal structure.
```typescript
// BAD: Tests implementation details
test("checkout calls paymentService.process", async () => {
const mockPayment = jest.mock(paymentService);
await checkout(cart, payment);
expect(mockPayment.process).toHaveBeenCalledWith(cart.total);
});
```
Red flags:
- Mocking internal collaborators
- Testing private methods
- Asserting on call counts/order
- Test breaks when refactoring without behavior change
- Test name describes HOW not WHAT
- Verifying through external means instead of interface
```typescript
// BAD: Bypasses interface to verify
test("createUser saves to database", async () => {
await createUser({ name: "Alice" });
const row = await db.query("SELECT * FROM users WHERE name = ?", ["Alice"]);
expect(row).toBeDefined();
});
// GOOD: Verifies through interface
test("createUser makes user retrievable", async () => {
const user = await createUser({ name: "Alice" });
const retrieved = await getUser(user.id);
expect(retrieved.name).toBe("Alice");
});
```
**Tautological tests**: Expected value restates the implementation, so the test passes by construction.
```typescript
// BAD: Expected value is recomputed the way the code computes it
test("calculateTotal sums line items", () => {
const items = [{ price: 10 }, { price: 5 }];
const expected = items.reduce((sum, i) => sum + i.price, 0);
expect(calculateTotal(items)).toBe(expected);
});
// GOOD: Expected value is an independent, known literal
test("calculateTotal sums line items", () => {
expect(calculateTotal([{ price: 10 }, { price: 5 }])).toBe(15);
});
```

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# GLOSSARY.md Format
`GLOSSARY.md` is the canonical language for this teaching workspace. All explainers, exercises, and learning records should adhere to its terminology. Building it is itself part of learning: compressing a concept into a tight definition is evidence the user understands it.
## Structure
```md
# {Topic} Glossary
{One or two sentence description of the topic this glossary covers.}
## Terms
**Hypertrophy**:
Muscle growth driven by mechanical tension and metabolic stress over repeated training sessions.
_Avoid_: Bulking, getting big
**Progressive overload**:
Systematically increasing the demand on a muscle over time — via load, volume, or intensity.
_Avoid_: Pushing harder, levelling up
**RPE (Rate of Perceived Exertion)**:
A 110 self-rating of how hard a set felt, where 10 is failure and 8 means two reps left in the tank.
_Avoid_: Effort score, intensity rating
```
## Rules
- **Add a term only when the user understands it.** The glossary is a record of compressed knowledge, not a dictionary the user reads to learn. If the user has just been introduced to a concept, wait until they can use it correctly before promoting it here.
- **Be opinionated.** When several words exist for the same concept, pick the best one and list the rest as aliases to avoid. This is how language compresses.
- **Keep definitions tight.** One or two sentences. Define what the term IS, not what it does or how to do it.
- **Use the glossary's own terms inside definitions.** Once a term is in the glossary, prefer it everywhere — including inside other definitions. This is what makes complex terms easier to grasp later.
- **Group under subheadings** when natural clusters emerge (e.g. `## Anatomy`, `## Programming`). A flat list is fine when terms cohere.
- **Flag ambiguities explicitly.** If a term is used loosely in the wider field, note the resolution: "In this workspace, 'set' always means a working set — warm-ups are tracked separately."
- **Revise as understanding deepens.** A definition the user wrote in week one may be wrong by week six. Update in place; do not leave stale entries.

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# Learning Record Format
Learning records live in `./learning-records/` and use sequential numbering: `0001-slug.md`, `0002-slug.md`, etc. Create the directory lazily — only when the first record is written.
They are the teaching equivalent of ADRs: they capture non-obvious lessons, key insights, and stated prior knowledge that will steer future sessions. They are used to calculate the zone of proximal development.
## Template
```md
# {Short title of what was learned or established}
{1-3 sentences: what was learned (or what prior knowledge was established), and why it matters for future sessions.}
```
That is the whole format. A learning record can be a single paragraph. The value is recording _that_ this is now known and _why_ it changes what to teach next — not in filling out sections.
## Optional sections
Only include these when they add genuine value. Most records won't need them.
- **Status** frontmatter (`active | superseded by LR-NNNN`) — useful when an earlier understanding turns out to be wrong and is replaced.
- **Evidence** — how the user demonstrated the understanding (a question answered, an exercise completed, prior experience cited). Useful when the claim might be revisited.
- **Implications** — what this unlocks or rules out for future sessions. Worth recording when non-obvious.
## Numbering
Scan `./learning-records/` for the highest existing number and increment by one.
## When to write a learning record
Write one when any of these is true:
1. **The user demonstrated genuine understanding of something non-trivial** — not just exposure, but evidence they can use the concept correctly. This sets a new floor for what to teach next.
2. **The user disclosed prior knowledge** — "I already know X." Record it so future sessions don't re-teach it. Also record the _depth_ claimed.
3. **A misconception was corrected** — the user previously believed something wrong and now sees why. These are high-value: they predict future stumbling blocks for related topics.
4. **The mission shifted in response to learning** — the user discovered they cared about something different than they thought. Cross-link to [[MISSION.md]] and update it.
### What does _not_ qualify
- Material that was merely covered. Coverage is not learning. Wait for evidence.
- Anything already captured tersely in [[GLOSSARY.md]] as a term definition. Don't duplicate.
- Session-by-session activity logs. Learning records are not a journal — they are decision-grade insights.
## Supersession
When a later record contradicts an earlier one (the user's understanding deepened or corrected), mark the old record `Status: superseded by LR-NNNN` rather than deleting it. The history of how understanding evolved is itself useful signal.

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# MISSION.md Format
`MISSION.md` lives at the workspace root. It captures the _reason_ the user is learning this topic. Every teaching decision — what to teach next, which resources to surface, which exercises to design — should trace back to this document.
## Template
```md
# Mission: {Topic}
## Why
{1-3 sentences. The concrete real-world goal the user is chasing. What changes in their life or work when they have this skill? Avoid abstract framings like "to understand X" — push for the underlying outcome.}
## Success looks like
- {A specific, observable thing the user will be able to do}
- {Another specific thing}
- {…}
## Constraints
- {Time, budget, prior commitments, learning preferences, anything that bounds the approach}
## Out of scope
- {Adjacent topics the user explicitly does not want to chase right now — protects the zone of proximal development}
```
## Rules
- **One mission per workspace.** If the user wants to learn two unrelated things, that is two workspaces.
- **Concrete over abstract.** "Run a half marathon by October" beats "get fitter." "Ship a Rust CLI to my team" beats "learn Rust."
- **Push back on vagueness.** If the user cannot articulate why, interview them before writing anything. A bad mission is worse than no mission.
- **Revise when reality shifts.** Missions change. When the user's goal moves, update this file — don't leave a stale mission steering future sessions.
- **Keep it short.** If `MISSION.md` runs past a screen, it has stopped being a compass and started being a plan.

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# RESOURCES.md Format
`RESOURCES.md` is the curated set of trusted sources for this topic. Knowledge for explainers should be drawn from here, not from parametric guesses. Wisdom comes from the communities listed here.
## Structure
```md
# {Topic} Resources
## Knowledge
- [Book: _The Science and Practice of Strength Training_ — Zatsiorsky & Kraemer](https://example.com)
Foundational text on programming and adaptation. Use for: anything to do with periodisation, recovery, intensity zones.
- [Article: "How Much Should I Train?" — Greg Nuckols (Stronger By Science)](https://example.com)
Evidence-based review of volume landmarks. Use for: weekly set targets per muscle group.
## Wisdom (Communities)
- [r/weightroom](https://reddit.com/r/weightroom)
High-signal subreddit, moderated against bro-science. Use for: programme critique, plateau troubleshooting.
- Local: Tuesday strength class at {gym name}
Use for: real-time coaching feedback on lifts.
```
## Rules
- **High-trust only.** Prefer primary sources, recognised experts, peer-reviewed work, and communities with strong moderation. If a resource is marketing dressed as education, leave it out.
- **Annotate every entry.** A bare link is useless in three months. Add one line: what it covers and when to reach for it.
- **Group by Knowledge / Wisdom.** Mirrors the philosophy in [SKILL.md](./SKILL.md). It is fine for a resource to appear in only one group.
- **Surface gaps explicitly.** If no good resource exists for an area the mission needs, write a `## Gaps` section listing what is missing. This drives future search.
- **Prune ruthlessly.** A resource that turned out to be wrong, shallow, or off-mission should be removed, not buried. Better five sharp sources than thirty mediocre ones.
- **Record community preferences.** If the user has opted out of joining communities, note it here so future sessions don't keep proposing them.

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---
name: teach
description: Teach the user a new skill or concept, within this workspace.
disable-model-invocation: true
argument-hint: "What would you like to learn about?"
---
The user has asked you to teach them something. This is a stateful request - they intend to learn the topic over multiple sessions.
## Teaching Workspace
Treat the current directory as a teaching workspace. The state of their learning is captured in this directory in several files:
- `MISSION.md`: A document capturing the _reason_ the user is interested in the topic. This should be used to ground all teaching. Use the format in [MISSION-FORMAT.md](./MISSION-FORMAT.md).
- `./reference/*.html`: A directory of reference materials. These are the compressed learnings from the lessons - cheat sheets, reference algorithms, syntax, yoga poses, glossaries. They are the raw units of learning. They should be beautiful documents which print out well, and are designed for quick reference.
- `RESOURCES.md`: A list of resources which can be explored to ground your teaching in contextual knowledge, or to acquire knowledge and wisdom. Use the format in [RESOURCES-FORMAT.md](./RESOURCES-FORMAT.md).
- `./learning-records/*.md`: A directory of learning records, which capture what the user has learned. These are loosely equivalent to architectural decision records in software development - they capture non-obvious lessons and key insights that may need to be revised later, or drive future sessions. These should be used to calculate the zone of proximal development. They are titled `0001-<dash-case-name>.md`, where the number increments each time. Use the format in [LEARNING-RECORD-FORMAT.md](./LEARNING-RECORD-FORMAT.md).
- `./lessons/*.html`: A directory of lessons. A **lesson** is a single, self-contained HTML output that teaches one tightly-scoped thing tied to the mission. This is the primary unit of teaching in this workspace.
- `./assets/*`: Reusable **components** shared across lessons. See [Assets](#assets).
- `NOTES.md`: A scratchpad for you to jot down user preferences, or working notes.
## Philosophy
To learn at a deep level, the user needs three things:
- **Knowledge**, captured from high-quality, high-trust resources
- **Skills**, acquired through highly-relevant interactive lessons devised by you, based on the knowledge
- **Wisdom**, which comes from interacting with other learners and practitioners
Before the `RESOURCES.md` is well-populated, your focus should be to find high-quality resources which will help the user acquire knowledge. Never trust your parametric knowledge.
Some topics may require more skills than knowledge. Learning more about theoretical physics might be more knowledge-based. For yoga, more skills-based.
### Fluency vs Storage Strength
You should be careful to split between two types of learning:
- **Fluency strength**: in-the-moment retrieval of knowledge
- **Storage strength**: long-term retention of knowledge
Fluency can give the user an illusory sense of mastery, but storage strength is the real goal. Try to design lessons which build long-term retention by desirable difficulty:
- Using retrieval practice (recall from memory)
- Spacing (distributing practice over time)
- Interleaving (mixing up different but related topics in practice - for skills practice only)
## Lessons
A lesson is the main thing you produce — the unit in which knowledge and skills reach the user. Each lesson is one self-contained HTML file, saved to `./lessons/` and titled `0001-<dash-case-name>.html` where the number increments each time.
A lesson should be **beautiful** — clean, readable typography and layout — since the user will return to these later to review. Think Tufte.
The lesson should be short, and completable very quickly. Learners' working memory is very small, and we need to stay within it. But each lesson should give the user a single tangible win that they can build on. It should be directly tied to the mission, and should be in the user's zone of proximal development.
If possible, open the lesson file for the user by running a CLI command.
Each lesson should link via HTML anchors to other lessons and reference documents.
Each lesson should recommend a primary source for the user to read or watch. This should be the most high-quality, high-trust resource you found on the topic.
Each lesson should contain a reminder to ask followup questions to the agent. The agent is their teacher, and can assist with anything that's unclear.
## Assets
Lessons are built from reusable **components**, stored in `./assets/`: stylesheets, quiz widgets, simulators, diagram helpers — anything a second lesson could reuse.
Reuse is the default, not the exception. Before authoring a lesson, read `./assets/` and build from the components already there. When a lesson needs something new and reusable, write it as a component in `./assets/` and link to it — never inline code a future lesson would duplicate.
A shared stylesheet is the first component every workspace earns: every lesson links it, so the lessons look like one consistent course rather than a pile of one-offs. As the workspace grows, so should the component library.
## The Mission
Every lesson should be tied into the mission - the reason that the user is interested in learning about the topic.
If the user is unclear about the mission, or the `MISSION.md` is not populated, your first job should be to question the user on why they want to learn this.
Failing to understand the mission will mean knowledge acquisition is not grounded in real-world goals. Lessons will feel too abstract. You will have no way of judging what the user should do next.
Missions may change as the user develops more skills and knowledge. This is normal - make sure to update the `MISSION.md` and add a learning record to capture the change. Confirm with the user before changing the mission.
## Zone Of Proximal Development
Each lesson, the user should always feel as if they are being challenged 'just enough'.
The user may specify an exact thing they want to learn. If they don't, figure out their zone of proximal development by:
- Reading their `learning-records`
- Figuring out the right thing to teach them based on their mission
- Teach the most relevant thing that fits in their zone of proximal development
## Knowledge
Lessons should be designed around a skill the user is going to learn. The knowledge in the lesson should be only what's required to acquire that skill. You teach the knowledge first, then get the user to practice the skills via an interactive feedback loop.
Knowledge should first be gathered from trusted resources. Use `RESOURCES.md` to keep track of them. Lessons should be littered with citations - links to external resources to back up any claim made. This increases the trustworthiness of the lesson.
For acquiring knowledge, difficulty is the enemy. It eats working memory you need for understanding.
## Skills
If knowledge is all about acquisition, skills are about durability and flexibility. Make the knowledge stick.
For skill acquisition, difficulty is the tool. Effortful retrieval is what builds storage strength. Skills should be taught through interactive lessons. There are several tools at your disposal:
- Interactive lessons, using quizzes and light in-browser tasks
- Lessons which guide the user through a list of real-world steps to take (for instance, yoga poses)
Each of these should be based on a **feedback loop**, where the user receives feedback on their performance. This feedback loop should be as tight as possible, giving feedback immediately - and ideally automatically.
For quizzes, each answer should be exactly the same number of words (and characters, if possible). Don't give the user any clues about the answer through formatting.
## Acquiring Wisdom
Wisdom comes from true real-world interaction - testing your skills outside the learning environment.
When the user asks a question that appears to require wisdom, your default posture should be to attempt to answer - but to ultimately delegate to a **community**.
A community is a place (online or offline) where the user can test their skills in the real world. This might be a forum, a subreddit, a real-world class (budget permitting) or a local interest group.
You should attempt to find high-reputation communities the user can join. If the user expresses a preference that they don't want to join a community, respect it.
## Reference Documents
While creating lessons, you should also create reference documents. Lessons can reference these documents - they are useful for tracking raw units of knowledge useful across lessons.
Lessons will rarely be revisited later - reference documents will be. They should be the compressed essence of the lesson, in a format designed for quick reference.
Some learning topics lend themselves to reference:
- Syntax and code snippets for programming
- Algorithms and flowcharts for processes
- Yoga poses and sequences for yoga
- Exercises and routines for fitness
- Glossaries for any topic with its own nomenclature
Glossaries, in particular, are an essential reference. Once one is created, it should be adhered to in every lesson.
## `NOTES.md`
The user will sometimes express preferences of how they want to be taught, or things you should keep in mind. This is the place to record those preferences, so you can refer back to them when designing lessons or working with the user.

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---
name: to-issues
description: Break a plan, spec, or PRD into independently-grabbable issues on the project issue tracker using tracer-bullet vertical slices.
disable-model-invocation: true
---
# To Issues
Break a plan into independently-grabbable issues using vertical slices (tracer bullets).
The issue tracker and triage label vocabulary should have been provided to you — run `/setup-matt-pocock-skills` if not.
## Process
### 1. Gather context
Work from whatever is already in the conversation context. If the user passes an issue reference (issue number, URL, or path) as an argument, fetch it from the issue tracker and read its full body and comments.
### 2. Explore the codebase (optional)
If you have not already explored the codebase, do so to understand the current state of the code. Issue titles and descriptions should use the project's domain glossary vocabulary, and respect ADRs in the area you're touching.
Look for opportunities to prefactor the code to make the implementation easier. "Make the change easy, then make the easy change."
### 3. Draft vertical slices
Break the plan into **tracer bullet** issues. Each issue is a thin vertical slice that cuts through ALL integration layers end-to-end, NOT a horizontal slice of one layer.
<vertical-slice-rules>
- Each slice delivers a narrow but COMPLETE path through every layer (schema, API, UI, tests)
- A completed slice is demoable or verifiable on its own
- Any prefactoring should be done first
</vertical-slice-rules>
### 4. Quiz the user
Present the proposed breakdown as a numbered list. For each slice, show:
- **Title**: short descriptive name
- **Blocked by**: which other slices (if any) must complete first
- **User stories covered**: which user stories this addresses (if the source material has them)
Ask the user:
- Does the granularity feel right? (too coarse / too fine)
- Are the dependency relationships correct?
- Should any slices be merged or split further?
Iterate until the user approves the breakdown.
### 5. Publish the issues to the issue tracker
For each approved slice, publish a new issue to the issue tracker. Use the issue body template below. These issues are considered ready for AFK agents, so publish them with the correct triage label unless instructed otherwise.
Publish issues in dependency order (blockers first) so you can reference real issue identifiers in the "Blocked by" field.
<issue-template>
## Parent
A reference to the parent issue on the issue tracker (if the source was an existing issue, otherwise omit this section).
## What to build
A concise description of this vertical slice. Describe the end-to-end behavior, not layer-by-layer implementation.
Avoid specific file paths or code snippets — they go stale fast. Exception: if a prototype produced a snippet that encodes a decision more precisely than prose can (state machine, reducer, schema, type shape), inline it here and note briefly that it came from a prototype. Trim to the decision-rich parts — not a working demo, just the important bits.
## Acceptance criteria
- [ ] Criterion 1
- [ ] Criterion 2
- [ ] Criterion 3
## Blocked by
- A reference to the blocking ticket (if any)
Or "None - can start immediately" if no blockers.
</issue-template>
Do NOT close or modify any parent issue.

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---
name: to-prd
description: Turn the current conversation into a PRD and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.
disable-model-invocation: true
---
This skill takes the current conversation context and codebase understanding and produces a PRD. Do NOT interview the user — just synthesize what you already know.
The issue tracker and triage label vocabulary should have been provided to you — run `/setup-matt-pocock-skills` if not.
## Process
1. Explore the repo to understand the current state of the codebase, if you haven't already. Use the project's domain glossary vocabulary throughout the PRD, and respect any ADRs in the area you're touching.
2. Sketch out the seams at which you're going to test the feature. Existing seams should be preferred to new ones. Use the highest seam possible. If new seams are needed, propose them at the highest point you can. The fewer seams across the codebase, the better - the ideal number is one.
Check with the user that these seams match their expectations.
3. Write the PRD using the template below, then publish it to the project issue tracker. Apply the `ready-for-agent` triage label - no need for additional triage.
<prd-template>
## Problem Statement
The problem that the user is facing, from the user's perspective.
## Solution
The solution to the problem, from the user's perspective.
## User Stories
A LONG, numbered list of user stories. Each user story should be in the format of:
1. As an <actor>, I want a <feature>, so that <benefit>
<user-story-example>
1. As a mobile bank customer, I want to see balance on my accounts, so that I can make better informed decisions about my spending
</user-story-example>
This list of user stories should be extremely extensive and cover all aspects of the feature.
## Implementation Decisions
A list of implementation decisions that were made. This can include:
- The modules that will be built/modified
- The interfaces of those modules that will be modified
- Technical clarifications from the developer
- Architectural decisions
- Schema changes
- API contracts
- Specific interactions
Do NOT include specific file paths or code snippets. They may end up being outdated very quickly.
Exception: if a prototype produced a snippet that encodes a decision more precisely than prose can (state machine, reducer, schema, type shape), inline it within the relevant decision and note briefly that it came from a prototype. Trim to the decision-rich parts — not a working demo, just the important bits.
## Testing Decisions
A list of testing decisions that were made. Include:
- A description of what makes a good test (only test external behavior, not implementation details)
- Which modules will be tested
- Prior art for the tests (i.e. similar types of tests in the codebase)
## Out of Scope
A description of the things that are out of scope for this PRD.
## Further Notes
Any further notes about the feature.
</prd-template>

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---
name: to-spec
description: Turn the current conversation into a spec and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.
disable-model-invocation: true
---
This skill takes the current conversation context and codebase understanding and produces a spec (you may know this document as a PRD). Do NOT interview the user — just synthesize what you already know.
The issue tracker and triage label vocabulary should have been provided to you — run `/setup-matt-pocock-skills` if not.
## Process
1. Explore the repo to understand the current state of the codebase, if you haven't already. Use the project's domain glossary vocabulary throughout the spec, and respect any ADRs in the area you're touching.
2. Sketch out the seams at which you're going to test the feature. Existing seams should be preferred to new ones. Use the highest seam possible. If new seams are needed, propose them at the highest point you can. The fewer seams across the codebase, the better - the ideal number is one.
Check with the user that these seams match their expectations.
3. Write the spec using the template below, then publish it to the project issue tracker. Apply the `ready-for-agent` triage label - no need for additional triage.
<spec-template>
## Problem Statement
The problem that the user is facing, from the user's perspective.
## Solution
The solution to the problem, from the user's perspective.
## User Stories
A LONG, numbered list of user stories. Each user story should be in the format of:
1. As an <actor>, I want a <feature>, so that <benefit>
<user-story-example>
1. As a mobile bank customer, I want to see balance on my accounts, so that I can make better informed decisions about my spending
</user-story-example>
This list of user stories should be extremely extensive and cover all aspects of the feature.
## Implementation Decisions
A list of implementation decisions that were made. This can include:
- The modules that will be built/modified
- The interfaces of those modules that will be modified
- Technical clarifications from the developer
- Architectural decisions
- Schema changes
- API contracts
- Specific interactions
Do NOT include specific file paths or code snippets. They may end up being outdated very quickly.
Exception: if a prototype produced a snippet that encodes a decision more precisely than prose can (state machine, reducer, schema, type shape), inline it within the relevant decision and note briefly that it came from a prototype. Trim to the decision-rich parts — not a working demo, just the important bits.
## Testing Decisions
A list of testing decisions that were made. Include:
- A description of what makes a good test (only test external behavior, not implementation details)
- Which modules will be tested
- Prior art for the tests (i.e. similar types of tests in the codebase)
## Out of Scope
A description of the things that are out of scope for this spec.
## Further Notes
Any further notes about the feature.
</spec-template>

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---
name: to-tickets
description: Break a plan, spec, or the current conversation into a set of tracer-bullet tickets, each declaring its blocking edges, published to the configured tracker — edges as text in a local file, or native blocking links on a real tracker.
disable-model-invocation: true
---
# To Tickets
Break a plan, spec, or conversation into a set of **tickets** — tracer-bullet vertical slices, each declaring the tickets that **block** it.
The issue tracker and triage label vocabulary should have been provided to you — run `/setup-matt-pocock-skills` if not.
## Process
### 1. Gather context
Work from whatever is already in the conversation context. If the user passes a reference (a spec path, an issue number or URL) as an argument, fetch it and read its full body and comments.
### 2. Explore the codebase (optional)
If you have not already explored the codebase, do so to understand the current state of the code. Ticket titles and descriptions should use the project's domain glossary vocabulary, and respect ADRs in the area you're touching.
Look for opportunities to prefactor the code to make the implementation easier. "Make the change easy, then make the easy change."
### 3. Draft vertical slices
Break the work into **tracer bullet** tickets.
<vertical-slice-rules>
- Each slice cuts a narrow but COMPLETE path through every layer (schema, API, UI, tests) — vertical, NOT a horizontal slice of one layer
- A completed slice is demoable or verifiable on its own
- Each slice is sized to fit in a single fresh context window
- Any prefactoring should be done first
</vertical-slice-rules>
Give each ticket its **blocking edges** — the other tickets that must complete before it can start. A ticket with no blockers can start immediately.
**Wide refactors are the exception to vertical slicing.** A **wide refactor** is one mechanical change — rename a column, retype a shared symbol — whose **blast radius** fans across the whole codebase, so a single edit breaks thousands of call sites at once and no vertical slice can land green. Don't force it into a tracer bullet; sequence it as **expandcontract**. First expand: add the new form beside the old so nothing breaks. Then migrate the call sites over in batches sized by blast radius (per package, per directory), each batch its own ticket blocked by the expand, keeping CI green batch to batch because the old form still exists. Finally contract: delete the old form once no caller remains, in a ticket blocked by every migrate batch. When even the batches can't stay green alone, keep the sequence but let them share an integration branch that all block a final integrate-and-verify ticket — green is promised only there.
### 4. Quiz the user
Present the proposed breakdown as a numbered list. For each ticket, show:
- **Title**: short descriptive name
- **Blocked by**: which other tickets (if any) must complete first
- **What it delivers**: the end-to-end behaviour this ticket makes work
Ask the user:
- Does the granularity feel right? (too coarse / too fine)
- Are the blocking edges correct — does each ticket only depend on tickets that genuinely gate it?
- Should any tickets be merged or split further?
Iterate until the user approves the breakdown.
### 5. Publish the tickets to the configured tracker
Publish the approved tickets. **How** depends on the tracker `/setup-matt-pocock-skills` configured — the tickets are the same either way, only the shape of the blocking edges changes:
- **Local files** → write one `tickets.md` in the repo root, all tickets in dependency order (blockers first), each with its "Blocked by" listing the titles it depends on. Use the file template below.
- **A real issue tracker (GitHub, Linear, …)** → publish one issue per ticket in dependency order (blockers first) so each ticket's blocking edges can reference real identifiers. Use the platform's native blocking / sub-issue relationship where it has one; otherwise set each ticket's "Blocked by" to the blocking issues. Apply the `ready-for-agent` triage label unless instructed otherwise — the tickets are agent-grabbable by construction.
Do NOT close or modify any parent issue.
<tickets-file-template>
# Tickets: <short name of the work>
A one-line summary of what these tickets build. Reference the source spec if there is one.
Work the **frontier**: any ticket whose blockers are all done. For a purely linear chain that means top to bottom.
## <Ticket title>
**What to build:** the end-to-end behaviour this ticket makes work, from the user's perspective — not a layer-by-layer implementation list.
**Blocked by:** the titles of the tickets that gate this one, or "None — can start immediately".
- [ ] Acceptance criterion 1
- [ ] Acceptance criterion 2
## <Ticket title>
...
</tickets-file-template>
<issue-template>
## Parent
A reference to the parent issue on the tracker (if the source was an existing issue, otherwise omit this section).
## What to build
The end-to-end behaviour this ticket makes work, from the user's perspective — not layer-by-layer implementation.
## Acceptance criteria
- [ ] Criterion 1
- [ ] Criterion 2
## Blocked by
- A reference to each blocking ticket, or "None — can start immediately".
</issue-template>
In either form, avoid specific file paths or code snippets — they go stale fast. Exception: if a prototype produced a snippet that encodes a decision more precisely than prose can (state machine, reducer, schema, type shape), inline it and note briefly that it came from a prototype. Trim to the decision-rich parts — not a working demo, just the important bits.
Work the frontier one ticket at a time with `/implement`, clearing context between tickets.
</content>

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# Writing Agent Briefs
An agent brief is a structured comment posted on a GitHub issue or PR when it moves to `ready-for-agent`. It is the authoritative specification that an AFK agent will work from. The original body and discussion are context — the agent brief is the contract.
The brief states **what the agent should do**, which stretches to both surfaces: for an issue, that's building the change from nothing; for a PR, it's what's left to do *to the existing diff* — finish it, close gaps, address review points. Same principles either way; the PR example below shows the difference.
## Principles
### Durability over precision
The issue may sit in `ready-for-agent` for days or weeks. The codebase will change in the meantime. Write the brief so it stays useful even as files are renamed, moved, or refactored.
- **Do** describe interfaces, types, and behavioral contracts
- **Do** name specific types, function signatures, or config shapes that the agent should look for or modify
- **Don't** reference file paths — they go stale
- **Don't** reference line numbers
- **Don't** assume the current implementation structure will remain the same
### Behavioral, not procedural
Describe **what** the system should do, not **how** to implement it. The agent will explore the codebase fresh and make its own implementation decisions.
- **Good:** "The `SkillConfig` type should accept an optional `schedule` field of type `CronExpression`"
- **Bad:** "Open src/types/skill.ts and add a schedule field on line 42"
- **Good:** "When a user runs `/triage` with no arguments, they should see a summary of issues needing attention"
- **Bad:** "Add a switch statement in the main handler function"
### Complete acceptance criteria
The agent needs to know when it's done. Every agent brief must have concrete, testable acceptance criteria. Each criterion should be independently verifiable.
- **Good:** "Running `gh issue list --label needs-triage` returns issues that have been through initial classification"
- **Bad:** "Triage should work correctly"
### Explicit scope boundaries
State what is out of scope. This prevents the agent from gold-plating or making assumptions about adjacent features.
## Template
```markdown
## Agent Brief
**Category:** bug / enhancement
**Summary:** one-line description of what needs to happen
**Current behavior:**
Describe what happens now. For bugs, this is the broken behavior.
For enhancements, this is the status quo the feature builds on.
**Desired behavior:**
Describe what should happen after the agent's work is complete.
Be specific about edge cases and error conditions.
**Key interfaces:**
- `TypeName` — what needs to change and why
- `functionName()` return type — what it currently returns vs what it should return
- Config shape — any new configuration options needed
**Acceptance criteria:**
- [ ] Specific, testable criterion 1
- [ ] Specific, testable criterion 2
- [ ] Specific, testable criterion 3
**Out of scope:**
- Thing that should NOT be changed or addressed in this issue
- Adjacent feature that might seem related but is separate
```
## Examples
### Good agent brief (bug)
```markdown
## Agent Brief
**Category:** bug
**Summary:** Skill description truncation drops mid-word, producing broken output
**Current behavior:**
When a skill description exceeds 1024 characters, it is truncated at exactly
1024 characters regardless of word boundaries. This produces descriptions
that end mid-word (e.g. "Use when the user wants to confi").
**Desired behavior:**
Truncation should break at the last word boundary before 1024 characters
and append "..." to indicate truncation.
**Key interfaces:**
- The `SkillMetadata` type's `description` field — no type change needed,
but the validation/processing logic that populates it needs to respect
word boundaries
- Any function that reads SKILL.md frontmatter and extracts the description
**Acceptance criteria:**
- [ ] Descriptions under 1024 chars are unchanged
- [ ] Descriptions over 1024 chars are truncated at the last word boundary
before 1024 chars
- [ ] Truncated descriptions end with "..."
- [ ] The total length including "..." does not exceed 1024 chars
**Out of scope:**
- Changing the 1024 char limit itself
- Multi-line description support
```
### Good agent brief (enhancement)
```markdown
## Agent Brief
**Category:** enhancement
**Summary:** Add `.out-of-scope/` directory support for tracking rejected feature requests
**Current behavior:**
When a feature request is rejected, the issue is closed with a `wontfix` label
and a comment. There is no persistent record of the decision or reasoning.
Future similar requests require the maintainer to recall or search for the
prior discussion.
**Desired behavior:**
Rejected feature requests should be documented in `.out-of-scope/<concept>.md`
files that capture the decision, reasoning, and links to all issues that
requested the feature. When triaging new issues, these files should be
checked for matches.
**Key interfaces:**
- Markdown file format in `.out-of-scope/` — each file should have a
`# Concept Name` heading, a `**Decision:**` line, a `**Reason:**` line,
and a `**Prior requests:**` list with issue links
- The triage workflow should read all `.out-of-scope/*.md` files early
and match incoming issues against them by concept similarity
**Acceptance criteria:**
- [ ] Closing a feature as wontfix creates/updates a file in `.out-of-scope/`
- [ ] The file includes the decision, reasoning, and link to the closed issue
- [ ] If a matching `.out-of-scope/` file already exists, the new issue is
appended to its "Prior requests" list rather than creating a duplicate
- [ ] During triage, existing `.out-of-scope/` files are checked and surfaced
when a new issue matches a prior rejection
**Out of scope:**
- Automated matching (human confirms the match)
- Reopening previously rejected features
- Bug reports (only enhancement rejections go to `.out-of-scope/`)
```
### Good agent brief (PR)
For a PR, "Current behavior" describes the state of the diff, and the brief asks the agent to finish or fix it rather than build from scratch.
```markdown
## Agent Brief
**Category:** enhancement
**Summary:** Finish the contributor's `--json` output flag for `triage list`
**Current behavior:**
The PR adds a `--json` flag that serializes the issue list to JSON. The happy
path works and the diff matches the project's command structure. Two gaps
remain: errors are still printed as human text (not JSON), and the new flag has
no test coverage.
**Desired behavior:**
With `--json`, all output — including errors — is well-formed JSON on stdout,
and the command's exit codes are unchanged. The existing human-readable output
is untouched when the flag is absent.
**Key interfaces:**
- The command's error path should emit `{ "error": string }` under `--json`
instead of the plain-text error
- Reuse the existing serializer the PR already added; don't introduce a second
**Acceptance criteria:**
- [ ] `triage list --json` emits valid JSON for both success and error cases
- [ ] Exit codes match the non-JSON command
- [ ] A test covers the `--json` success output and one error case
- [ ] Default (non-JSON) output is byte-for-byte unchanged
**Out of scope:**
- Adding `--json` to any other command
- Changing the JSON shape of the success payload the PR already defined
```
### Bad agent brief
```markdown
## Agent Brief
**Summary:** Fix the triage bug
**What to do:**
The triage thing is broken. Look at the main file and fix it.
The function around line 150 has the issue.
**Files to change:**
- src/triage/handler.ts (line 150)
- src/types.ts (line 42)
```
This is bad because:
- No category
- Vague description ("the triage thing is broken")
- References file paths and line numbers that will go stale
- No acceptance criteria
- No scope boundaries
- No description of current vs desired behavior

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# Out-of-Scope Knowledge Base
The `.out-of-scope/` directory in a repo stores persistent records of rejected feature requests. It serves two purposes:
1. **Institutional memory** — why a feature was rejected, so the reasoning isn't lost when the issue is closed
2. **Deduplication** — when a new issue comes in that matches a prior rejection, the skill can surface the previous decision instead of re-litigating it
## Directory structure
```
.out-of-scope/
├── dark-mode.md
├── plugin-system.md
└── graphql-api.md
```
One file per **concept**, not per issue. Multiple issues requesting the same thing are grouped under one file.
## File format
The file should be written in a relaxed, readable style — more like a short design document than a database entry. Use paragraphs, code samples, and examples to make the reasoning clear and useful to someone encountering it for the first time.
```markdown
# Dark Mode
This project does not support dark mode or user-facing theming.
## Why this is out of scope
The rendering pipeline assumes a single color palette defined in
`ThemeConfig`. Supporting multiple themes would require:
- A theme context provider wrapping the entire component tree
- Per-component theme-aware style resolution
- A persistence layer for user theme preferences
This is a significant architectural change that doesn't align with the
project's focus on content authoring. Theming is a concern for downstream
consumers who embed or redistribute the output.
```ts
// The current ThemeConfig interface is not designed for runtime switching:
interface ThemeConfig {
colors: ColorPalette; // single palette, resolved at build time
fonts: FontStack;
}
```
## Prior requests
- #42 — "Add dark mode support"
- #87 — "Night theme for accessibility"
- #134 — "Dark theme option"
```
### Naming the file
Use a short, descriptive kebab-case name for the concept: `dark-mode.md`, `plugin-system.md`, `graphql-api.md`. The name should be recognizable enough that someone browsing the directory understands what was rejected without opening the file.
### Writing the reason
The reason should be substantive — not "we don't want this" but why. Good reasons reference:
- Project scope or philosophy ("This project focuses on X; theming is a downstream concern")
- Technical constraints ("Supporting this would require Y, which conflicts with our Z architecture")
- Strategic decisions ("We chose to use A instead of B because...")
The reason should be durable. Avoid referencing temporary circumstances ("we're too busy right now") — those aren't real rejections, they're deferrals.
## When to check `.out-of-scope/`
During triage (Step 1: Gather context), read all files in `.out-of-scope/`. When evaluating a new issue:
- Check if the request matches an existing out-of-scope concept
- Matching is by concept similarity, not keyword — "night theme" matches `dark-mode.md`
- If there's a match, surface it to the maintainer: "This is similar to `.out-of-scope/dark-mode.md` — we rejected this before because [reason]. Do you still feel the same way?"
The maintainer may:
- **Confirm** — the new issue gets added to the existing file's "Prior requests" list, then closed
- **Reconsider** — the out-of-scope file gets deleted or updated, and the issue proceeds through normal triage
- **Disagree** — the issues are related but distinct, proceed with normal triage
## When to write to `.out-of-scope/`
Only when an **enhancement** (not a bug) is *rejected* as `wontfix`. This applies to enhancement PRs exactly as it does to issues — a rejected PR is recorded here so the same request doesn't return as fresh code.
Do **not** write here when something is closed as `wontfix` because it's **already implemented**. That's a built feature, not a rejected one; recording it would poison the dedup checks with false rejections. Instead, the closing comment points to where the feature already lives.
The flow:
1. Maintainer decides a feature request is out of scope
2. Check if a matching `.out-of-scope/` file already exists
3. If yes: append the new issue to the "Prior requests" list
4. If no: create a new file with the concept name, decision, reason, and first prior request
5. Post a comment on the issue explaining the decision and mentioning the `.out-of-scope/` file
6. Close the issue with the `wontfix` label
## Updating or removing out-of-scope files
If the maintainer changes their mind about a previously rejected concept:
- Delete the `.out-of-scope/` file
- The skill does not need to reopen old issues — they're historical records
- The new issue that triggered the reconsideration proceeds through normal triage

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---
name: triage
description: Move issues and external PRs through a state machine of triage roles — categorise, verify, grill if needed, and write agent-ready briefs.
disable-model-invocation: true
---
# Triage
Move issues on the project issue tracker through a small state machine of triage roles.
If this repo treats external pull requests as a request surface (see the issue-tracker config), triage covers them too: **a PR is an issue with attached code** — same roles, same states, same machine, with a few deltas marked "for a PR" below. Resolve a bare `#42` to an issue or PR per the tracker config.
Every comment or issue posted to the issue tracker during triage **must** start with this disclaimer:
```
> *This was generated by AI during triage.*
```
## Reference docs
- [AGENT-BRIEF.md](AGENT-BRIEF.md) — how to write durable agent briefs
- [OUT-OF-SCOPE.md](OUT-OF-SCOPE.md) — how the `.out-of-scope/` knowledge base works
## Roles
Two **category** roles:
- `bug` — something is broken
- `enhancement` — new feature or improvement
Five **state** roles:
- `needs-triage` — maintainer needs to evaluate
- `needs-info` — waiting on reporter for more information
- `ready-for-agent` — fully specified, ready for an AFK agent
- `ready-for-human` — needs human implementation
- `wontfix` — will not be actioned
For a PR, the same states read against the attached code: `ready-for-agent` means a brief is attached and an agent should take the next step on the diff; `ready-for-human` means it's ready for a human to merge.
Every triaged issue should carry exactly one category role and one state role. If state roles conflict, flag it and ask the maintainer before doing anything else.
These are canonical role names — the actual label strings used in the issue tracker may differ. The mapping should have been provided to you - run `/setup-matt-pocock-skills` if not.
State transitions: an unlabeled issue normally goes to `needs-triage` first; from there it moves to `needs-info`, `ready-for-agent`, `ready-for-human`, or `wontfix`. `needs-info` returns to `needs-triage` once the reporter replies. The maintainer can override at any time — flag transitions that look unusual and ask before proceeding.
## Invocation
The maintainer invokes `/triage` and describes what they want in natural language. Interpret the request and act. Examples:
- "Show me anything that needs my attention"
- "Let's look at #42" (issue or PR)
- "Move #42 to ready-for-agent"
- "What's ready for agents to pick up?"
## Show what needs attention
Query the issue tracker and present three buckets, oldest first:
1. **Unlabeled** — never triaged.
2. **`needs-triage`** — evaluation in progress.
3. **`needs-info` with reporter activity since the last triage notes** — needs re-evaluation.
When PRs are in scope, include external PRs in these buckets and tag each line `[PR]` or `[issue]`. Discovery surfaces only *external* PRs (the tracker config defines who counts as external) — a collaborator's in-flight PR is not triage work. This filter is discovery-only; an explicitly named PR is always triaged regardless of author.
Show counts and a one-line summary per item. Let the maintainer pick.
## Triage a specific issue or PR
1. **Gather context.** Read the full issue or PR (body, comments, labels, author, dates; for a PR, the diff too). Parse any prior triage notes so you don't re-ask resolved questions. Explore the codebase using the project's domain glossary, respecting ADRs in the area. Run two checks against the codebase: (a) **redundancy** — search for an existing implementation of the requested behavior by domain concept (not just the request's wording), and report where you looked. If found, it's an already-implemented `wontfix` (step 5). (b) **prior rejection** — read `.out-of-scope/*.md` and surface any that resembles this request.
2. **Recommend.** Tell the maintainer your category and state recommendation with reasoning, plus a brief codebase summary relevant to the request — including whether it's already implemented. Wait for direction.
3. **Verify the claim.** Before any grilling, check that the claim holds up. For a bug, reproduce it from the reporter's steps. For a PR, confirm the diff does what it claims — check it out, run the relevant tests or commands. Report what happened: confirmed (with code path), failed, or insufficient detail (a strong `needs-info` signal). A confirmed verification makes a much stronger agent brief.
4. **Grill (if needed).** If the request needs fleshing out, run the `/grilling` and `/domain-modeling` skills together — grill it into shape one question at a time, sharpening domain terms and updating `CONTEXT.md`/ADRs inline as decisions land.
5. **Apply the outcome:**
- `ready-for-agent` — post an agent brief comment ([AGENT-BRIEF.md](AGENT-BRIEF.md)).
- `ready-for-human` — same structure as an agent brief, but note why it can't be delegated (judgment calls, external access, design decisions, manual testing).
- `needs-info` — post triage notes (template below).
- `wontfix` — close, with the comment depending on *why*:
- **Already implemented** — the change already exists in the codebase. Point to where it lives; do **not** write to `.out-of-scope/` (that KB is for *rejected* requests, not built ones).
- **Rejected (bug)** — polite explanation, then close.
- **Rejected (enhancement)** — write to `.out-of-scope/`, link to it from a comment, then close ([OUT-OF-SCOPE.md](OUT-OF-SCOPE.md)).
- `needs-triage` — apply the role. Optional comment if there's partial progress.
## Quick state override
If the maintainer says "move #42 to ready-for-agent", trust them and apply the role directly. Confirm what you're about to do (role changes, comment, close), then act. Skip grilling. If moving to `ready-for-agent` without a grilling session, ask whether they want to write an agent brief.
## Needs-info template
```markdown
## Triage Notes
**What we've established so far:**
- point 1
- point 2
**What we still need from you (@reporter):**
- question 1
- question 2
```
Capture everything resolved during grilling under "established so far" so the work isn't lost. Questions must be specific and actionable, not "please provide more info".
## Resuming a previous session
If prior triage notes exist on the issue or PR, read them, check whether the reporter has answered any outstanding questions, and present an updated picture before continuing. Don't re-ask resolved questions.

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---
name: ubiquitous-language
description: Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".
disable-model-invocation: true
---
# Ubiquitous Language
Extract and formalize domain terminology from the current conversation into a consistent glossary, saved to a local file.
## Process
1. **Scan the conversation** for domain-relevant nouns, verbs, and concepts
2. **Identify problems**:
- Same word used for different concepts (ambiguity)
- Different words used for the same concept (synonyms)
- Vague or overloaded terms
3. **Propose a canonical glossary** with opinionated term choices
4. **Write to `UBIQUITOUS_LANGUAGE.md`** in the working directory using the format below
5. **Output a summary** inline in the conversation
## Output Format
Write a `UBIQUITOUS_LANGUAGE.md` file with this structure:
```md
# Ubiquitous Language
## Order lifecycle
| Term | Definition | Aliases to avoid |
| ----------- | ------------------------------------------------------- | --------------------- |
| **Order** | A customer's request to purchase one or more items | Purchase, transaction |
| **Invoice** | A request for payment sent to a customer after delivery | Bill, payment request |
## People
| Term | Definition | Aliases to avoid |
| ------------ | ------------------------------------------- | ---------------------- |
| **Customer** | A person or organization that places orders | Client, buyer, account |
| **User** | An authentication identity in the system | Login, account |
## Relationships
- An **Invoice** belongs to exactly one **Customer**
- An **Order** produces one or more **Invoices**
## Example dialogue
> **Dev:** "When a **Customer** places an **Order**, do we create the **Invoice** immediately?"
> **Domain expert:** "No — an **Invoice** is only generated once a **Fulfillment** is confirmed. A single **Order** can produce multiple **Invoices** if items ship in separate **Shipments**."
> **Dev:** "So if a **Shipment** is cancelled before dispatch, no **Invoice** exists for it?"
> **Domain expert:** "Exactly. The **Invoice** lifecycle is tied to the **Fulfillment**, not the **Order**."
## Flagged ambiguities
- "account" was used to mean both **Customer** and **User** — these are distinct concepts: a **Customer** places orders, while a **User** is an authentication identity that may or may not represent a **Customer**.
```
## Rules
- **Be opinionated.** When multiple words exist for the same concept, pick the best one and list the others as aliases to avoid.
- **Flag conflicts explicitly.** If a term is used ambiguously in the conversation, call it out in the "Flagged ambiguities" section with a clear recommendation.
- **Only include terms relevant for domain experts.** Skip the names of modules or classes unless they have meaning in the domain language.
- **Keep definitions tight.** One sentence max. Define what it IS, not what it does.
- **Show relationships.** Use bold term names and express cardinality where obvious.
- **Only include domain terms.** Skip generic programming concepts (array, function, endpoint) unless they have domain-specific meaning.
- **Group terms into multiple tables** when natural clusters emerge (e.g. by subdomain, lifecycle, or actor). Each group gets its own heading and table. If all terms belong to a single cohesive domain, one table is fine — don't force groupings.
- **Write an example dialogue.** A short conversation (3-5 exchanges) between a dev and a domain expert that demonstrates how the terms interact naturally. The dialogue should clarify boundaries between related concepts and show terms being used precisely.
<example>
## Example dialogue
> **Dev:** "How do I test the **sync service** without Docker?"
> **Domain expert:** "Provide the **filesystem layer** instead of the **Docker layer**. It implements the same **Sandbox service** interface but uses a local directory as the **sandbox**."
> **Dev:** "So **sync-in** still creates a **bundle** and unpacks it?"
> **Domain expert:** "Exactly. The **sync service** doesn't know which layer it's talking to. It calls `exec` and `copyIn` — the **filesystem layer** just runs those as local shell commands."
</example>
## Re-running
When invoked again in the same conversation:
1. Read the existing `UBIQUITOUS_LANGUAGE.md`
2. Incorporate any new terms from subsequent discussion
3. Update definitions if understanding has evolved
4. Re-flag any new ambiguities
5. Rewrite the example dialogue to incorporate new terms

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---
name: wayfinder
description: Plan a huge chunk of work — more than one agent session can hold — as a shared map of investigation tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.
disable-model-invocation: true
---
A loose idea has arrived — too big for one agent session, and wrapped in fog: the way from here to the **destination** isn't visible yet. Wayfinding is about finding that way, not charging at the destination. This skill charts the way as a **shared map** on the repo's issue tracker, then works its tickets one at a time until the route is clear.
The destination varies per effort, and naming it is the first act of charting — it shapes every ticket. It might be a spec to hand off and iterate on, a decision to lock before planning starts, or a change made in place like a data-structure migration. The map is domain-agnostic — engineering work, course content, whatever fits the shape.
## Plan, don't do
Wayfinder is **planning** by default: each ticket resolves a decision, and the map is done when the way is clear — nothing left to decide before someone goes and does the thing. The pull to just do the work is usually the signal you've reached the edge of the map and it's time to hand off. An effort can override this in its **Notes** — carrying execution into the map itself — but absent that, produce decisions, not deliverables.
## Refer by name
Every map and ticket is an issue, so it has a **name** — its title. In everything the human reads — narration, the map's Decisions-so-far — refer to it by that name, never by a bare id, number, or slug. A wall of `#42, #43, #44` is illegible; names read at a glance. The id and URL don't vanish — a name wraps its link — but they ride *inside* the name, never stand in for it.
## The Map
The map is a single issue on this repo's issue tracker, labelled `wayfinder:map` — the canonical artifact. Its tickets are child issues of the map.
The map is an **index**, not a store. It lists the decisions made and points at the tickets that hold their detail; a decision lives in exactly one place — its ticket — so the map never restates it, only gists it and links.
**Where the map, its child tickets, blocking, and frontier queries physically live is tracker-specific.** The issue tracker should have been provided to you — run `/setup-matt-pocock-skills` if not. Consult the tracker doc's "Wayfinding operations" section for how _this_ repo expresses them. If no tracker has been provided, default to the local-markdown tracker.
### The map body
The whole map at low resolution, loaded once per session. Open tickets are **not** listed — they are open child issues, found by query.
```markdown
## Destination
<what reaching the end of this map looks like the spec, decision, or change this effort is finding its way to. One or two lines; every session orients to it before choosing a ticket.>
## Notes
<domain; skills every session should consult; standing preferences for this effort>
## Decisions so far
<!-- the index — one line per closed ticket: enough to judge relevance, then zoom the link for the detail the ticket holds -->
- [<closed ticket title>](link) — <one-line gist of the answer>
## Not yet specified
<!-- see "Fog of war": in-scope fog you can't ticket yet; graduates as the frontier advances -->
## Out of scope
<!-- see "Out of scope": work ruled beyond the destination; closed, never graduates -->
```
### Tickets
Each ticket is a **child issue** of the map; the tracker's issue id is its identity. Its body is the question, sized to one 100K token agent session:
```markdown
## Question
<the decision or investigation this ticket resolves>
```
Each ticket carries a `wayfinder:<type>` label — one of `research`, `prototype`, `grilling`, `task` (see [Ticket Types](#ticket-types)).
A session **claims** a ticket by assigning it to the dev driving the map, **first**, before any work, so concurrent sessions skip it. That assignee _is_ the claim: an open, unassigned ticket is unclaimed.
Blocking uses the tracker's **native** dependency relationship — essential because it renders the frontier _visually_ in the tracker's own UI, so the human sees what's takeable without opening the map. Only a tracker that lacks native blocking falls back to a body convention. A ticket is **unblocked** when every ticket blocking it is closed; the **frontier** is the open, unblocked, unclaimed children — the edge of the known.
The answer isn't part of the body — it's recorded on resolution (see [Work through the map](#work-through-the-map)). Assets created while resolving a ticket are linked from the issue, not pasted in.
## Ticket Types
Every ticket is either **HITL** — human in the loop, worked *with* a human who speaks for themselves — or **AFK**, driven by the agent alone. A HITL ticket only resolves through that live exchange; the agent never stands in for the human's side of it (a grilling agent that answers its own questions has broken this).
- **Research** (AFK): Reading documentation, third-party APIs, or local resources like knowledge bases. Creates a markdown summary as a linked asset. Use when knowledge outside the current working directory is required.
- **Prototype** (HITL): Raise the fidelity of the discussion by making a cheap, rough, concrete artifact to react to — an outline, a rough take, a stub, or UI/logic code via the /prototype skill. Links the prototype as an asset. Use when "how should it look" or "how should it behave" is the key question.
- **Grilling** (HITL): Conversation via the /grilling and /domain-modeling skills, one question at a time. The default case.
- **Task** (HITL or AFK): Manual work that must happen before a *decision* can be made — nothing to decide, prototype, or research, but the discussion is blocked until it's done. Signing up for a service so its API can be judged, provisioning access, moving data so its shape can be seen. This is the one type that *does* rather than decides — and it earns its place by unblocking a decision, not by delivering the destination. The agent drives it alone where it can (AFK); otherwise it hands the human a precise checklist (HITL). Resolved when the work is done; the answer records what was done and any resulting facts (credentials location, new URLs, row counts) later tickets depend on.
## Fog of war
The map is _deliberately_ incomplete: don't chart what you can't yet see. Beyond the live tickets lies the **fog of war** — the dim view of decisions and investigations you can tell are coming but can't yet pin down, because they hang on questions still open. Resolving a ticket clears the fog ahead of it, graduating whatever's now specifiable into fresh tickets — one at a time, until the way to the destination is clear and no tickets remain.
The map's **Not yet specified** section is where that dim view is written down: the suspected question, the area to revisit later. It's the undiscovered frontier _toward_ the destination — everything here is in scope, just not sharp enough to ticket. Write as loosely or as fully as the view allows; it doubles as a signpost for collaborators reading where the effort is headed.
**Fog or ticket?** The test is whether you can state the question precisely now — _not_ whether you can answer it now.
- **Ticket when** the question is already sharp — even if it's blocked and you can't act on it yet.
- **Not yet specified when** you can't yet phrase it that sharply. Don't pre-slice the fog into ticket-sized pieces: it's coarser than a ticket, and one patch may graduate into several tickets, or none, once the frontier reaches it.
**Not yet specified** excludes what's already decided (Decisions so far), what's already a live ticket, and what's out of scope (the next section).
## Out of scope
Fog only ever gathers _toward_ the destination. The destination fixes the scope, so work beyond it is **out of scope** — it isn't fog, and it doesn't belong in **Not yet specified**. It gets its own **Out of scope** section on the map: work you've consciously ruled out of _this_ effort. Scope, not sharpness, lands it here.
Out-of-scope work never graduates — the frontier stops at the destination — so it returns only if the destination is redrawn, and then as a fresh effort, not a resumption.
Ruling something out of scope is a scoping act, not a step on the route. When a ticket that already exists turns out to sit past the destination — mis-scoped in while charting, or exposed by a resolution — **close it** (a closed ticket is unambiguously off the frontier) and leave one line in the **Out of scope** section: the gist plus why it's out of scope, linking the closed ticket. It stays out of **Decisions so far**, which records the route actually walked — a scope boundary isn't a step on it.
## Invocation
Two modes. Either way, **never resolve more than one ticket per session.**
### Chart the map
User invokes with a loose idea.
1. **Name the destination.** Run a `/grilling` and `/domain-modeling` session to pin down what this map is finding its way to — the spec, decision, or change. The destination fixes the scope, so it's settled first.
2. **Map the frontier.** Grill again, **breadth-first** this time: fan out across the whole space rather than deep on any one thread, surfacing the open decisions and the first steps takeable now. **If this surfaces no fog** — the way to the destination is already clear, the whole journey small enough for one session — you don't need a map. Stop and ask the user how they'd like to proceed.
3. **Create the map** (label `wayfinder:map`): Destination and Notes filled in, Decisions-so-far empty, the fog sketched into **Not yet specified**.
4. **Create the tickets you can specify now** as child issues of the map — then wire blocking edges in a **second pass** (issues need ids before they can reference each other). Wiring sorts them into the frontier and the blocked; everything you can't yet specify stays in the fog — the **Not yet specified** section.
5. Stop — charting the map is one session's work; do not also resolve tickets.
### Work through the map
User invokes with a map (URL or number). A ticket is **optional** — without one, you pick the next decision, not the user.
1. Load the **map** — the low-res view, not every ticket body.
2. Choose the ticket. If the user named one, use it. Otherwise take the first frontier ticket in order. **Claim it**: assign it to yourself before any work.
3. Resolve it — **zoom as needed**: fetch the full body of any related or closed ticket on demand; invoke the skills the `## Notes` block names. If in doubt, use `/grilling` and `/domain-modeling`.
4. Record the resolution: post the answer as a **resolution comment**, **close** the issue, and **append a context pointer** to the map's Decisions-so-far.
5. Add newly-surfaced tickets (create-then-wire); graduate any fog the answer has made specifiable, clearing each graduated patch from **Not yet specified** so it lives only as its new ticket. If the answer reveals a ticket — this one or another — sits beyond the destination, **rule it out of scope** rather than resolving it on the route. If the decision invalidates other parts of the map, update or delete those tickets.
The user may run unblocked tickets in parallel, so expect other sessions to be editing the tracker concurrently.

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---
name: wizard
description: Generate an interactive bash wizard that walks a human through a manual procedure — third-party setup, a one-off migration, an A→B state transition — opening URLs, capturing values, confirming each step, and writing .env files and GitHub Actions secrets.
disable-model-invocation: true
---
# Wizard
A **wizard** is a bash script that walks a human, step by step, through a manual procedure that's tedious to do by hand and tedious to re-explain to an AI every time. It opens each URL, says exactly what to click and copy, captures the values, writes them where they belong (`.env`, GitHub secrets), confirms at every stage, and shows how much is left. It might configure third-party services, run a one-off migration, or move the project from one state to another.
The delightful UX is already solved by [template.sh](template.sh) — progress with time-remaining, confirmation gates, cross-platform URL opening (including WSL), hidden secret entry, idempotent `.env` upserts, `gh secret`/`gh variable` writes, and a closing summary. **Your job is only to scope the procedure and author its stages.** The library above the `STAGES` marker is identical in every wizard; that consistency is the point — never hand-edit it.
A wizard is ephemeral by default — built for one run, saved to a scratch or `scripts/` path, deleted when the job's done. Commit it only when the user wants a repeatable setup path that should live in the repo.
## Process
### 1. Scope the procedure
Work out every manual step the human must take and every value that gets captured along the way. Read the repo first — don't ask cold:
- For setup: `.env`, `.env.example`, `.env.*`, `README`, `docker-compose*`, framework config, and `.github/workflows/*` (every `secrets.*` / `vars.*` reference is a value the wizard must produce).
- For a migration or transition: the current state, the target state, and the irreversible actions between them.
Then show the user the ordered list of stages and the values each produces, and confirm — they may add, drop, or reorder.
**Done when:** every stage is named in order, and for each captured value you know (a) where the human gets it, (b) where it's written (`.env`, a GitHub secret, both, or nowhere — some stages are pure actions), and (c) whether it's secret (hidden entry) or public.
### 2. Map each stage's journey
For each stage, write the precise path a human follows: which URL to open, what to do there, where a value is shown, which variable it fills — e.g. "Dashboard → Developers → API keys → Reveal test key → copy". Where you don't actually know the current UI or the exact command, say so and ask the user or check the docs — never invent steps that may not exist.
**Done when:** every stage traces to concrete instructions a stranger could follow.
### 3. Author the wizard
Copy `template.sh` to the target path. Replace the example stage with one `stage` per step, in dependency order. Use the library helpers — `stage`, `say`/`step`, `open_url`, `ask`/`ask_secret`, `write_env`, `set_secret`/`set_var`, `pause`/`confirm` — and set `TOTAL_STAGES` and `TOTAL_MINUTES` to honest estimates (this drives the time-remaining display).
Hold the bar the template sets: open the URL before asking for its value, use `ask_secret` for anything secret, `write_env` every persisted value, `set_secret` only the values CI actually needs, and `confirm` before any irreversible action. Each `stage` clears the screen so only the current step is visible — keep a stage to one focused task so nothing the human needs scrolls away. Don't touch the library above the marker.
### 4. Verify and hand off
- `bash -n <script>`; run `shellcheck` if available.
- `chmod +x <script>`.
- Don't run it end-to-end yourself — it opens browsers and blocks on human input. Trace it statically instead: every value from step 1 is captured and lands where step 1 said, and every `set_secret` name exactly matches a `secrets.*` reference in CI.
- Tell the user how to run it. If it's a repeatable setup path, commit it and link it from the README so the next person runs the script instead of asking an AI.

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#!/usr/bin/env bash
#
# A wizard — walks a human through a manual procedure step by step.
# Generated by the /wizard skill.
#
# Everything above the "STAGES" marker is the wizard library: do not hand-edit
# it. Author the per-step stages below the marker.
set -euo pipefail
# ──────────────────────────────────────────────────────────────────────────
# Wizard library — delightful, consistent UX. Identical across every wizard.
# ──────────────────────────────────────────────────────────────────────────
if [[ -t 1 ]] && command -v tput >/dev/null 2>&1 && [[ "$(tput colors 2>/dev/null || echo 0)" -ge 8 ]]; then
BOLD=$(tput bold); DIM=$(tput dim); RESET=$(tput sgr0)
BLUE=$(tput setaf 4); GREEN=$(tput setaf 2); YELLOW=$(tput setaf 3); RED=$(tput setaf 1)
else
BOLD=""; DIM=""; RESET=""; BLUE=""; GREEN=""; YELLOW=""; RED=""
fi
# Author sets these two at the top of the stages section.
TOTAL_STAGES=0
TOTAL_MINUTES=0
_STAGE_INDEX=0
_MINUTES_ELAPSED=0
ENV_FILE="${ENV_FILE:-.env}"
WRITTEN_ENV=() # KEYs written to ENV_FILE this run
WRITTEN_SECRET=() # secret NAMEs set this run
SKIPPED=() # things we couldn't do (e.g. gh missing)
# _clear — wipe the terminal so only the current step is on screen. No-op when
# output isn't a terminal, so piped logs stay readable.
_clear() {
[[ -t 1 ]] || return 0
if command -v tput >/dev/null 2>&1; then tput clear; else printf '\033[2J\033[3J\033[H'; fi
}
# banner "Title" — opening frame: what this wizard does and how long it takes.
banner() {
_clear
printf '\n%s%s %s%s\n' "$BOLD" "$BLUE" "$1" "$RESET"
printf '%s %s stages · about %s minutes%s\n\n' \
"$DIM" "$TOTAL_STAGES" "$TOTAL_MINUTES" "$RESET"
printf '%s You drive the browser; this wizard tells you exactly what to do and\n' "$DIM"
printf ' captures the values you copy back. Stop any time with Ctrl-C and re-run\n'
printf ' later — it remembers values already saved.%s\n' "$RESET"
pause "Ready to start?"
}
# stage "Name" <minutes> — clear the screen, then announce a stage and show
# progress + time remaining. Clearing keeps only the current step on screen.
stage() {
_clear
_STAGE_INDEX=$((_STAGE_INDEX + 1))
local remaining=$((TOTAL_MINUTES - _MINUTES_ELAPSED))
(( remaining < 0 )) && remaining=0
_MINUTES_ELAPSED=$((_MINUTES_ELAPSED + ${2:-0}))
printf '\n%s%s▸ Stage %s/%s · %s%s %s(~%s min left)%s\n' \
"$BOLD" "$BLUE" "$_STAGE_INDEX" "$TOTAL_STAGES" "$1" "$RESET" "$DIM" "$remaining" "$RESET"
}
# say "..." — a plain instruction line.
say() { printf ' %s\n' "$1"; }
# step "..." — a numbered-feeling action the human takes in the browser.
step() { printf ' %s•%s %s\n' "$BLUE" "$RESET" "$1"; }
note() { printf ' %s%s%s\n' "$DIM" "$1" "$RESET"; }
warn() { printf ' %s⚠ %s%s\n' "$YELLOW" "$1" "$RESET"; }
# open_url URL — open in the human's browser, cross-platform incl. WSL.
open_url() {
local url="$1"
printf ' %s↗ opening%s %s\n' "$GREEN" "$RESET" "$url"
{ if command -v wslview >/dev/null 2>&1; then wslview "$url"
elif command -v explorer.exe >/dev/null 2>&1; then explorer.exe "$url"
elif command -v xdg-open >/dev/null 2>&1; then xdg-open "$url"
elif command -v open >/dev/null 2>&1; then open "$url"
else warn "couldn't open a browser — visit it manually: $url"; fi
} >/dev/null 2>&1 || warn "couldn't open a browser — visit it manually: $url"
}
# pause "msg" — wait for the human to confirm they've done the manual part.
pause() {
printf ' %s%s%s ' "$DIM" "${1:-Press Enter to continue}" "$RESET"
read -r _ || true
}
# confirm "question" — y/N gate; returns success on yes.
confirm() {
local reply=""
printf ' %s? %s [y/N] ' "$YELLOW" "$1"
read -r reply || true
[[ "$reply" =~ ^[Yy] ]]
}
# _existing KEY — current value of KEY in ENV_FILE, if any.
_existing() {
[[ -f "$ENV_FILE" ]] || return 1
local line; line=$(grep -E "^${1}=" "$ENV_FILE" | tail -n1) || return 1
printf '%s' "${line#*=}"
}
# ask KEY "Prompt" — read a value into $KEY. Offers the existing .env value as
# a default on re-runs (Enter keeps it). Visible input (non-secret).
ask() {
local key="$1" prompt="$2" current input
current=$(_existing "$key" || true)
if [[ -n "$current" ]]; then
printf ' %s%s%s %s[Enter keeps current]%s ' "$BOLD" "$prompt" "$RESET" "$DIM" "$RESET"
else
printf ' %s%s%s ' "$BOLD" "$prompt" "$RESET"
fi
read -r input || true
[[ -z "$input" && -n "$current" ]] && input="$current"
printf -v "$key" '%s' "$input"
}
# ask_secret KEY "Prompt" — like ask, but input is hidden.
ask_secret() {
local key="$1" prompt="$2" current input
current=$(_existing "$key" || true)
if [[ -n "$current" ]]; then
printf ' %s%s%s %s[Enter keeps current]%s ' "$BOLD" "$prompt" "$RESET" "$DIM" "$RESET"
else
printf ' %s%s%s ' "$BOLD" "$prompt" "$RESET"
fi
read -rs input || true
printf '\n'
[[ -z "$input" && -n "$current" ]] && input="$current"
printf -v "$key" '%s' "$input"
}
# write_env KEY VALUE — upsert KEY=VALUE into ENV_FILE (creates it; replaces
# any existing line). Idempotent.
write_env() {
local key="$1" value="$2" tmp
touch "$ENV_FILE"
tmp=$(mktemp)
grep -vE "^${key}=" "$ENV_FILE" > "$tmp" || true
printf '%s=%s\n' "$key" "$value" >> "$tmp"
mv "$tmp" "$ENV_FILE"
WRITTEN_ENV+=("$key")
printf ' %s✓ wrote%s %s → %s\n' "$GREEN" "$RESET" "$key" "$ENV_FILE"
}
# set_secret NAME VALUE — set a GitHub Actions repo secret via gh. Falls back
# to a warning (and records it) if gh is unavailable or unauthenticated.
set_secret() {
local name="$1" value="$2"
if command -v gh >/dev/null 2>&1 && gh auth status >/dev/null 2>&1; then
if printf '%s' "$value" | gh secret set "$name" >/dev/null 2>&1; then
WRITTEN_SECRET+=("$name")
printf ' %s✓ set%s GitHub secret %s\n' "$GREEN" "$RESET" "$name"
return
fi
fi
SKIPPED+=("GitHub secret $name (set it manually: gh secret set $name)")
warn "skipped GitHub secret $name — gh not ready; set it later"
}
# set_var NAME VALUE — set a GitHub Actions repo variable (non-secret).
set_var() {
local name="$1" value="$2"
if command -v gh >/dev/null 2>&1 && gh auth status >/dev/null 2>&1; then
if gh variable set "$name" --body "$value" >/dev/null 2>&1; then
printf ' %s✓ set%s GitHub variable %s\n' "$GREEN" "$RESET" "$name"
return
fi
fi
SKIPPED+=("GitHub variable $name")
warn "skipped GitHub variable $name — gh not ready; set it later"
}
# finish — clear, then a closing summary of everything configured.
finish() {
_clear
printf '\n%s%s ✓ Setup complete%s\n' "$BOLD" "$GREEN" "$RESET"
(( ${#WRITTEN_ENV[@]} )) && note "wrote ${#WRITTEN_ENV[@]} value(s) to $ENV_FILE: ${WRITTEN_ENV[*]}"
(( ${#WRITTEN_SECRET[@]} )) && note "set ${#WRITTEN_SECRET[@]} GitHub secret(s): ${WRITTEN_SECRET[*]}"
if (( ${#SKIPPED[@]} )); then
printf '\n'; warn "still to do by hand:"
for s in "${SKIPPED[@]}"; do note " - $s"; done
fi
printf '\n'
}
# ──────────────────────────────────────────────────────────────────────────
# STAGES — author this section. One stage() per step the human takes.
# Replace the example below. Set the two totals to match the stages you write.
# ──────────────────────────────────────────────────────────────────────────
TOTAL_STAGES=1
TOTAL_MINUTES=5
banner "Stripe setup"
# ── Example stage: replace with your real steps ───────────────────────────
stage "Stripe — API keys" 5
say "We'll grab your Stripe test keys and store them for local dev + CI."
open_url "https://dashboard.stripe.com/test/apikeys"
step "On the API keys page, copy the Publishable key (starts pk_test_)."
ask STRIPE_PUBLISHABLE_KEY "Paste the publishable key:"
step "Click 'Reveal test key' on the Secret key row, then copy it."
ask_secret STRIPE_SECRET_KEY "Paste the secret key:"
write_env STRIPE_PUBLISHABLE_KEY "$STRIPE_PUBLISHABLE_KEY"
write_env STRIPE_SECRET_KEY "$STRIPE_SECRET_KEY"
set_secret STRIPE_SECRET_KEY "$STRIPE_SECRET_KEY" # CI needs this one
# ──────────────────────────────────────────────────────────────────────────
finish

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---
name: writing-beats
description: Writing, exploit — assemble raw material into a journey of beats, grounding each term before a beat leans on it.
disable-model-invocation: true
---
<what-to-do>
The user has passed (or will pass) a markdown file of raw material. This is **exploit**: the exploring is done, the pile is fixed — commit to a path through it and mine the pile to fill each beat.
If the user did not say where to save the article, ask once and remember the path.
Then run a beat-by-beat journey, choose-your-own-adventure style:
1. **Establish the prerequisites.** Before any beats, settle with the user what the audience already knows walking in — the concepts that are **grounded** from the start. Everything else must be grounded by a beat before a later beat can use it. See [Grounding](#grounding).
2. Write 23 candidate **starting beats**, drawn from the raw material. Each is a different entry point into the article. Each may only lean on grounded concepts; note what new concepts each one grounds. Show the user the beats before writing to the article file. The user picks one. Preview what beats that pick unlocks — as if the user is seeing a little way down the path.
3. Once the user picks a starting beat, write **only that beat** to the article file. A beat may be one sentence or several paragraphs — whatever that beat naturally is. Stop there.
4. Re-read the article file from disk. Then offer 23 candidate **next beats** — different directions the journey could pivot to from where the article now stands. Each must be reachable from the current grounded set; note what each one grounds.
5. Loop steps 35 until the article reaches a natural end.
</what-to-do>
<supporting-info>
## Grounding
Every **concept** has to be **grounded** before a beat can lean on it: the audience either walked in knowing it or met it in an earlier beat. A beat that reaches for an ungrounded concept loses the reader — that is the one move the journey can't make. The unit is the concept, not the word for it: a beat can lean on an idea the reader lacks even with no jargon in sight. Where a concept has a name — a **term** — grounding it means landing the idea and the term together.
A concept gets grounded one of two ways:
- **Prerequisite** — grounded before the first beat. The audience brings it. Fixed at the start.
- **Introduced** — a beat establishes it, and from then on it's grounded for every later beat.
So each beat does two jobs: it **requires** concepts that are already grounded, and it **grounds** new ones. Keep a running list of what's grounded so far, and update it each time a beat lands.
This is what shapes the choose-your-own-adventure. A candidate beat is only reachable if everything it requires is already grounded; picking a beat that grounds concept X unlocks every beat that was waiting on X. When you offer next beats, they must all be reachable from the current grounded set — and say what each one grounds, so the user can see which paths it opens.
The big lever is what you make a prerequisite versus what you ground inside the piece. Demand too much up front and you shut out readers who don't have it; ground too much inside and the early beats drown in definitions. Settle this with the user when you establish prerequisites, and revisit it whenever a tempting beat turns out to require a concept nothing has grounded yet — the fix is either a grounding beat before it, or promoting the concept to a prerequisite.
## What is a beat
A beat is one move in the journey. It does one thing — sets a scene, lands a point, asks a question, drops an aside, twists the angle. Then it stops, leaving the reader at a place where the next beat can pivot.
A beat is sized by what it needs:
- A single sentence if that's all the move is ("And then nothing happened for three weeks.").
- A short paragraph if the move needs setup.
- Multiple paragraphs if the beat is a self-contained vignette, argument, or example.
If a "beat" needs five paragraphs and three subheadings, it's not a beat — it's two beats glued together. Split it.
## Pulling from the pile
Pull material from the raw pile to populate each beat. You can paraphrase, split, recombine, or quote. The pile is a quarry.
## Ending the journey
The article ends when the journey is complete — not when the pile is empty. Most piles will have leftover fragments that don't make it in. That is fine; that is the point of having more raw material than you need.
## Writing rhythm
- Append one beat at a time. Never write ahead.
- Re-read the article file from disk before every write. Preserve user edits absolutely.
- If the user edits a previous beat substantially, let it change what comes next.
- If the user says "rewrite that beat" or "go back and try a different beat 3", do it — edit in place, leave the rest alone.
</supporting-info>

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---
name: writing-fragments
description: Writing, explore — mine raw fragments, no structure yet.
disable-model-invocation: true
---
<what-to-do>
This is pure **explore**: widen the space of what could be written without committing to structure — committing is _exploit_, a separate skill's job. Run a grilling session that produces fragments, interviewing the user relentlessly about whatever they want to write about. Imposing phases, outlines, or article structure is out of scope here.
As fragments emerge from either side of the conversation, append them to a single markdown file.
If the user did not pass a path, ask once where to save the document, then remember it for the rest of the session.
Capture fragments from the very first thing the user says, including the initial prompt.
On first write, put a single H1 at the top with a working title (it can change later) and nothing else — no metadata, no TOC, no date.
</what-to-do>
<supporting-info>
## What is a fragment
A fragment is any piece of text that might survive into the final article. It must be _readable by the author_ — the author can tell what it means — but it does not need to define its terms or be comprehensible to a cold reader. The bar is "is this a piece of good writing?", not "is this a self-contained argument?"
Fragments are deliberately heterogeneous. Examples of what could be a fragment:
- A sharp sentence you'd want to deploy somewhere but don't yet know where.
- A claim with a one-line justification.
- A vignette: a thing that happened, a code snippet, a scenario, an analogy.
- A half-thought: "something about how X feels like Y, work this out later."
- A quote, a piece of dialogue, an overheard line.
- A list of related observations that hang together by feel.
- A complaint, a confession, a punchline.
- A **leading word** — a compact metaphor or coinage the whole piece can hang on (one term that names the idea, the way _tracer bullets_ or _fog of war_ names a whole pattern).
Of these, the leading word is the most valuable fragment to land. It is load-bearing: name the right one in explore and it shapes the structure, the transitions, and the title later — paying dividends through the entire exploit phase. When the conversation circles a recurring idea, push to coin a word for it.
The novelist's diary is the model: years of unstructured noticings that later get mined for raw material. Fragments are noticings.
## File format
```markdown
# Working title
A first fragment lives here.
It can be multiple paragraphs. It can include lists, code, quotes — whatever
shape the fragment naturally takes.
---
A second fragment.
---
> A quoted line that the user wants to keep around.
A reaction to it.
---
- A cluster of related observations
- That hang together by feel
- And want to be near each other
```
Fragments are separated by a horizontal rule (`\n---\n`). No headings inside the body. No tags. No order beyond the order they were added.
## Writing rhythm
Append silently. Don't ask permission for each fragment. Mention what you added in passing ("adding that"), but don't interrupt the conversation with save dialogs.
Before every write: re-read the file from disk. The user may have edited, reordered, or deleted fragments between turns — preserve their changes. Never overwrite the file; only append (or, if the user asks, edit a specific fragment in place).
The user can say "cut the last one", "rewrite that one sharper", "merge those two" at any time. Treat those as first-class instructions.
</supporting-info>

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# Glossary — Building Great Skills
The domain model for what makes a skill great. A skill exists to wrangle determinism out of a stochastic system; the root virtue is **Predictability**, and every term below is a lever on it. This is the disclosed reference for [`writing-great-skills`](SKILL.md).
The terms are grouped by axis: **Invocation** (how a skill is reached), **Information Hierarchy** (how its content is arranged), **Steering** (how the agent's runtime behaviour is shaped), and **Pruning** (how it is kept lean). Each **failure mode** lives beside the lever that cures it, tagged _failure mode_.
**Bold terms** in any definition are themselves defined in this glossary; find them by their heading.
## Predictability
The degree to which a skill makes the agent behave the same _way_ on every run — the same process, not the same output (a brainstorming skill should _predictably_ diverge; its tokens vary, its behaviour doesn't). The root virtue every other term serves — cost and maintainability are symptoms of it, not rivals.
_Avoid_: consistency, reliability, robustness, output-determinism
## Invocation
How a skill is reached — and the two loads you pay for the choice.
### Model-Invoked
A skill that keeps its **description** field, so the agent can see it and fire it autonomously — and the human can still type its name, so model-invocation always _includes_ user reach. There is no model-only state: a description only ever _adds_ agent discovery, never removes the human's. Pays a permanent **context load** on every turn in exchange for that discoverability. Reachable by other skills, because the description that makes it agent-discoverable makes it invocable. A model-invoked skill whose content is all **reference** is also one home for shared reference: another skill can invoke it, so reference needed by several skills lives in one place. Pick model-invocation only when the agent must reach the skill on its own; if it never fires except by hand, drop the description and pay no context load.
_Avoid_: ability, tool, capability
### User-Invoked
A skill with its **description** stripped — invisible to the agent and reachable only by the human typing its name (user-_only_, where **model-invoked** is user-_and-agent_). Trades agent-discoverability for zero **context load**. Because it has no description, nothing but the human can reach it: no other skill can fire it.
_Avoid_: procedure, workflow, command
### Description
The skill's machine-readable trigger, and the one **context pointer** a **model-invoked** skill is forced to keep loaded at all times. Its mere presence _is_ the invocation axis: keep it and the skill is model-invoked (and reachable by other skills); delete it and the skill is **user-invoked**, reachable only by the human. The source of a model-invoked skill's **context load**.
_Avoid_: frontmatter, summary
### Context Pointer
A reference held in the agent's context that names some out-of-context material and encodes the condition for reaching it. The **description** is the top-level context pointer (context window → skill); pointers to disclosed files are the same object one level down. Its wording, not the target, decides _when_ the agent reaches — and _how reliably_. A must-have target behind a weakly worded pointer is a variance bug: fix the wording first, and inline the material only if sharpening fails.
_Avoid_: link, reference, import
### Context Load
The cost a **model-invoked** skill imposes on the agent's context window — its **description**, always loaded, spending both tokens and attention. What **user-invoked** skills escape by having no description, and the brake on splitting into more model-invoked skills.
_Avoid_: token cost, context bloat
### Cognitive Load
The cost a **user-invoked** skill imposes on the human — what they must hold in their head: which skills exist and when to reach for each (the human is the index). What **model-invocation** removes by being agent-discoverable, and the brake on splitting into more user-invoked skills. Not a cost to minimise: it is the price of human agency, the reason some skills stay user-invoked. Spend it where human judgement matters; remove it where it does not.
_Avoid_: human index, burden, overhead
### Router Skill
A **user-invoked** skill whose job is to point at your other user-invoked skills — naming each and when to reach for it — so the human has one skill to remember instead of many. It can only hint, never fire them: user-invoked skills have no **description**, so nothing but the human can reach them. The cure for **cognitive load** when user-invoked skills multiply.
_Avoid_: dispatcher, menu, registry, index, router procedure
### Granularity
How finely you divide skills. Finer division spends one of the two loads: more **model-invoked** skills spend **context load** (more descriptions crowding the window and competing for attention); more **user-invoked** skills spend **cognitive load** (more for the human to remember and reach for). Two cuts guide the division. By **invocation**, split off a model-invoked skill where you have a distinct **leading word** to trigger it — a trigger word you actually use in your prompts. By **sequence**, split a run of **steps** where a step's **post-completion steps** need hiding, since isolating it in its own context clears what follows. Beware the reverse: merging sequences exposes each step's post-completion steps to what follows, inviting premature completion.
_Avoid_: chunking, modularity
## Information Hierarchy
How a skill's content is arranged, and how far down the ladder each piece sits.
### Information Hierarchy
A skill's content ranked by how immediately the agent needs it — a single ladder, produced by two cuts: in-file or behind a pointer, and step or reference. The rungs:
- **Steps** — in-file, primary
- **Reference**, in-file — secondary
- **Reference**, disclosed — behind a **context pointer**
A skill with no **steps** uses just the bottom two rungs — often a legitimately flat peer-set (e.g. every rule of a review on one rung), which is a fine arrangement, not a smell. The hierarchy is independent of invocation: a skill can be model- or user-invoked whether it is all steps, all reference, or both. When a skill has steps, in-file reference that should be disclosed buries them and turns attending to them into a coin-flip — a variance lever, not just a legibility one. Keep the top of the ladder legible; push down it whatever you can.
_Avoid_: structure, organization, layout
### Steps
The ordered actions the agent performs — when a skill has them, the primary tier of its content, and the part that earns its place in SKILL.md. Not every skill has steps: a skill can be all steps (`tdd`), all **reference** (a review), or both, independent of invocation. Every step ends on a **completion criterion**, clear or vague.
_Avoid_: workflow, instructions, choreography
### Reference
Material the agent refers to on demand — definitions, facts, parameters, examples, conditional instructions. When a skill has **steps** it is secondary to them; when a skill has none it is the entire content; or it lives outside any skill entirely — see **External Reference**. Reached via **context pointers**, and the prime candidate for **progressive disclosure**.
_Avoid_: supporting material, docs, background
### External Reference
**Reference** that lives outside the skill system — a plain file, no **description**, no **steps**, not invocable — that any skill can point at. The home for shared reference that needn't fire on its own, and the only shared home two **user-invoked** skills can use, since neither has a description and so neither can fire the other.
_Avoid_: doc, resource, knowledge base
### Progressive Disclosure
Moving **reference** down the ladder — out of SKILL.md and behind a **context pointer** — so the top stays legible. Not primarily a token optimisation; it is how the **information hierarchy** is protected. Licensed by **branching**: disclose what only some branches need, inline what every path needs, and if a pointer fires unreliably on must-have material, sharpen its wording, and pull it back inline only if that fails.
_Avoid_: lazy loading, chunking
### Co-location
Keeping the material an agent needs at once in one place — a concept's definition, rules, and caveats under a single heading, not scattered across the file — so reading one part brings its neighbours with it. The within-file companion to the **Information Hierarchy**: the hierarchy ranks _how far down_ a piece sits; co-location decides _what sits beside it_ once there. There is no formula for the right format of a body of **reference**; the test is that a skill should read like documentation written for the agent, and grouped material reads that way where scattered material does not. Distinct from **Duplication**: that repeats one meaning in two places, where scattering fragments a single meaning across many.
_Avoid_: grouping, clustering, cohesion
### Sprawl
_Failure mode._ A skill that is simply too long — too many lines in SKILL.md — independent of whether they are stale or repeated. Even an all-live, all-unique skill can sprawl. It costs readability (the agent wades through more before it can act, and attention thins across the excess), maintainability (every extra line is one more to keep **relevant**), and tokens. The cure is the **information hierarchy**: push **reference** down behind **context pointers**, and split by **branch** or sequence so each path carries only what it needs. Distinct from **sediment** (length from stale accumulation) and **duplication** (length from repeated meaning) — sprawl is length itself, whatever its cause.
_Avoid_: bloat, length, size, verbosity
## Steering
The levers that shape the agent's runtime behaviour toward **Predictability**.
### Branch
A distinct way a skill can be invoked — a case the skill handles — so different runs take different paths through it. A skill with many steps may carry many branches; a linear one has none.
_Avoid_: path, case, fork
### Leading Word
A compact concept — also called a _Leitwort_ — already living in the model's pretraining, that the agent thinks with while running the skill. It encodes a behavioural principle in the fewest possible tokens by invoking priors the model already holds (e.g. _lesson_, _proximal zone of development_, _fog of war_, _tracer bullets_). Repeated as a token, never as a sentence, it accumulates a distributed definition across the skill and anchors a whole region of behaviour. Coining your own works if you define it clearly, but a made-up word recruits no priors — you pay in definition tokens what a pretrained word gives free. Reach for an existing word first.
A leading word serves **predictability** twice. In the body it anchors **execution** — the agent reaches for the same behaviour every time the concept appears, and inside flat reference it focuses attention on a class of thing to look for, recruiting the right checks each run. In the **description** it anchors **invocation** — and not only within the skill: when the same word lives in your prompts, your docs, and your codebase, the agent links that shared language to the skill and fires it more reliably. Word a description with the leading words you actually use when you want the skill.
_Avoid_: keyword, term, motif
### Completion Criterion
The condition that tells the agent a unit of work is done — the target it judges against. Two properties make it a lever, not just a quality. Its **clarity** (can the agent tell done from not-done?) resists **premature completion** — a vague bound ("understanding reached") lets the agent declare done and slip to the next step; this axis needs _steps_ to bite, since premature completion is a between-steps failure. Its **demand** (how much it requires) sets **legwork** — "every modified model accounted for" forces thorough work where "produce a change list" does not — and this axis is _not_ step-bound: it can bind a body of flat reference too, which is how a skill with no steps still carries an exhaustiveness bar ("every rule applied"). The strongest criteria are both checkable and exhaustive.
_Avoid_: done condition, exit condition, stopping rule
### Legwork
The work an agent does behind the scenes within a single step — reading files, exploring the codebase, making changes, digging up what it needs rather than offloading to the user. It lives below the step structure: never written as its own step, latent in the wording, controlled by the agent rather than the skill. The within-step counterpart to **post-completion steps**' across-step pull. Raised by a **leading word** (_comprehensive_, _thorough_) or a **completion criterion** that demands the work be exhaustive — including the demand axis applied to flat reference, which is what drives a skill of flat reference to cover all its rungs. Goes thin either when that demand is missing or when **premature completion** cuts the step short.
_Avoid_: scope, effort, diligence, coverage
### Post-Completion Steps
The **steps** that follow the current step. Visible, they pull the agent forward into **premature completion** — the more it sees, the stronger the tug; the defence is to hide them by splitting the sequence of steps into two.
_Avoid_: horizon, fog of war, lookahead
### Premature Completion
_Failure mode._ Ending the current step before it is genuinely done, because the agent's attention slips to being done rather than to the work. A between-steps failure: it needs **steps** to occur — a skill with no steps that quits early isn't premature completion but thin **legwork** under an unmet demand. A tug-of-war between two forces: visible **post-completion steps** (the pull forward) and the **completion criterion**'s clarity (the resistance — a sharp, checkable bar holds; a vague one gives way). Fuzziness is the necessary condition: a sharp bound resists the pull no matter how many later steps are visible, so a step that never rushes needs no defending. Two levers hold a step that does, but reach for them in order: **sharpen the bound first** — it is local and cheap. Only when the criterion is irreducibly fuzzy _and_ you actually observe the rush do you **hide the later steps** — and hiding only works across a real context boundary (a user-invoked hand-off or a subagent dispatch; an inline model-invoked call leaves the later steps in context and clears nothing). One cause of thin legwork, but distinct from it: legwork can be thin even when a step runs to full completion.
_Avoid_: premature closure, the rush, rushing, shortcutting
### Negation
_Failure mode._ Steering by prohibition — telling the agent what _not_ to do — which drags the forbidden behaviour into context and makes it _more_ available, not less. _Don't think of an elephant_, and the elephant is all there is; _never write verbose comments_, and verbosity is the pattern the agent has just read. The negation is a weak modifier the strongly-activated concept overruns, so the ban half-reads as an instruction to do the thing. Its **leading word** is the _elephant_: whatever a prohibition names into the frame. Cure: prompt the **positive** — describe the target behaviour ("write one-line comments") so the banned one is never spoken. A prohibition earns its place only as a hard guardrail on a behaviour you cannot phrase positively; even then, pair it with the positive target so attention lands on what to do.
_Avoid_: ironic rebound, don't-prompting, the pink elephant
## Pruning
Keeping a skill lean — each remedy paired with the failure it cures.
### Single Source of Truth
The desired state where each meaning lives in exactly one authoritative place, so a change to the skill's behaviour is a change in one place. **Duplication** is its violation.
_Avoid_: home, canonical location
### Duplication
_Failure mode._ The same meaning given more than one **single source of truth**. It costs maintenance (change one place, you must change the others), costs tokens, and inflates prominence — repeating a meaning weights it on the ladder past its real rank. The accidental inverse of a **leading word**, which raises attention on purpose by repeating a token, never the meaning.
_Avoid_: repetition, redundancy
### Relevance
Whether a line still bears on what the skill does — the lens for what to keep. A line loses relevance either by never bearing on the task (mere exposition, or a **branch** that should be disclosed) or by going stale: drifting out of date as the behaviour or world it describes changes. Shorter skills are easier to keep relevant, because each line is cheaper to check. Distinct from **no-op**: relevance asks whether a line bears on the task, not whether it changes behaviour.
_Avoid_: load-bearing, staleness, freshness
### Sediment
_Failure mode._ Layers of old content that settle in a skill and are never cleared, because adding feels safe and removing feels risky — so stale and irrelevant lines accumulate and you must core down through them to find what is still live. The default fate of any skill without a pruning discipline; the slow erosion of **relevance**, as opposed to **duplication**'s repeated meaning.
_Avoid_: accretion, bloat, cruft, rot
### No-Op
_Failure mode._ An instruction that changes nothing because the model already does it by default — you pay load to tell the agent what it would do anyway. The test: does a line change behaviour versus the default? A line can be perfectly **relevant** and still be a no-op. The same priors that make a **leading word** free make a no-op worthless.
A leading word is a _technique_; No-Op is a _verdict_ on a line — and they cross. A leading word too weak to beat the default is a no-op (_be thorough_ when the agent is already thorough-ish), and the fix is a stronger word that passes the verdict (_relentless_), not a different technique. So the No-Op test — does it change behaviour versus the default? — is also how you grade whether a leading word is earning its repetitions. This is model-relative, not reader-relative: two people disagreeing over whether a line is a no-op disagree about the default, and settle it by running the skill, not by debate.
_Avoid_: redundant instruction, restating the obvious, belaboring

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---
name: writing-great-skills
description: Reference for writing and editing skills well — the vocabulary and principles that make a skill predictable.
disable-model-invocation: true
---
A skill exists to wrangle determinism out of a stochastic system. **Predictability** — the agent taking the same _process_ every run, not producing the same output — is the root virtue; every lever below serves it.
**Bold terms** are defined in [`GLOSSARY.md`](GLOSSARY.md); look them up there for the full meaning.
## Invocation
Two choices, trading different costs:
- A **model-invoked** skill keeps a **description**, so the agent can fire it autonomously _and_ other skills can reach it (you can still type its name too). It contributes to **context load** — the description sits in the window every turn. Mechanics: omit `disable-model-invocation`, and write a model-facing description with rich trigger phrasing ("Use when the user wants…, mentions…").
- A **user-invoked** skill strips the description from the agent's reach: only you, typing its name, can invoke it — and no other skill can. Zero context load, but it spends **cognitive load**: _you_ are the index that must remember it exists. Mechanics: set `disable-model-invocation: true`; the `description` becomes human-facing — a one-line summary, trigger lists stripped.
Pick model-invocation only when the agent must reach the skill on its own, or another skill must. If it only ever fires by hand, make it user-invoked and pay no context load.
When user-invoked skills multiply past what you can remember, that piled-up cognitive load is cured by a **router skill**: one user-invoked skill that names the others and when to reach for each.
## Writing the description
A model-invoked **description** does two jobs — state what the skill is, and list the **branches** that should trigger it. Every word increases **context load**, so a description earns even harder pruning than the body:
- **Front-load the skill's leading word** — the description is where it does its invocation work.
- **One trigger per branch.** Synonyms that rename a single branch are **duplication** — "build features using TDD … asks for test-first development" is one branch written twice. Collapse them; keep only genuinely distinct branches.
- **Cut identity that's already in the body.** Keep the description to triggers, plus any "when another skill needs…" reach clause.
## Information hierarchy
A skill is built from two content types — **steps** and **reference** — that mix freely: a skill can be all steps, all reference, or both. The core decision is which to use and where each sits on the **information hierarchy**, a ladder ranked by how immediately the agent needs the material:
1. **In-skill step** — an ordered action in `SKILL.md`, the primary tier: what the agent does, in order. Each step ends on a **completion criterion**, the condition that tells the agent the work is done. Make it _checkable_ (can the agent tell done from not-done?) and, where it matters, _exhaustive_ ("every modified model accounted for", not "produce a change list") — a vague criterion invites **premature completion**.
2. **In-skill reference** — a definition, rule, or fact in `SKILL.md`, consulted on demand. Often a legitimately flat peer-set (every rule of a review on one rung) — a fine arrangement, not a smell. _This skill is all reference._
3. **External reference** — reference pushed out of `SKILL.md` into a separate file, reached by a **context pointer**, loaded only when the pointer fires. (Spans _disclosed_ reference — a sibling file like `GLOSSARY.md`, still part of the skill — through fully **external reference** that lives outside the skill system and any skill can point at.)
A demanding completion criterion drives thorough **legwork** — the digging the agent does within the work — whether the skill has steps or not, since "every rule applied" binds flat reference just as "every step done" binds a sequence.
Push too little down and the top bloats; push too much and you hide material the agent actually needs. That tension is the whole decision.
**Progressive disclosure** is the move down the ladder — out of `SKILL.md` into a linked file — so the top stays legible. Mechanics: a linked `.md` file in the skill folder, named for what it holds (this skill discloses its full definitions to `GLOSSARY.md`). Some skills are used in more than one way, and each distinct way is a **branch** — different runs taking different paths through the skill. Branching is the cleanest disclosure test: inline what every branch needs, and push behind a pointer what only some branches reach. A **context pointer**'s _wording_, not its target, decides when and how reliably the agent reaches the material.
Where the ladder decides _how far down_ a piece sits, **co-location** decides _what sits beside it_ once there: keep a concept's definition, rules, and caveats under one heading rather than scattered, so reading one part brings its neighbours with it.
## When to split
**Granularity** is how finely you divide skills, and each cut spends one of the two loads, so split only when the cut earns it. Two cuts:
- **By invocation** — split off a **model-invoked** skill when you have a distinct **leading word** that should trigger it on its own, or another skill must reach it. You pay **context load** for the new always-loaded **description**, so that independent reach has to be worth it.
- **By sequence** — split a run of **steps** when the steps still ahead (a step's **post-completion steps**) tempt the agent to rush the one in front of it (**premature completion**). Keeping them out of view encourages the agent to do more **legwork** on the current task.
## Pruning
Keep each meaning in a **single source of truth**: one authoritative place, so changing the behaviour is a one-place edit.
Check every line for **relevance**: does it still bear on what the skill does?
Then hunt **no-ops** sentence by sentence, not just line by line: run the no-op test on each sentence in isolation, and when one fails, delete the whole sentence rather than trim words from it. Be aggressive — most prose that fails should go, not be rewritten.
## Leading words
A **leading word** is a compact concept already living in the model's pretraining that the agent thinks with while running the skill (e.g. _lesson_, _fog of war_, _tracer bullets_). Repeated throughout the text (though not necessarily - a strong leading word might only be needed once), it accumulates a distributed definition and anchors a whole region of behaviour in the fewest tokens, by recruiting priors the model already holds.
It serves predictability twice. In the body it anchors _execution_: the agent reaches for the same behaviour every time the word appears. In the description it anchors _invocation_: when the same word lives in your prompts, docs, and code, the agent links that shared language to the skill and fires it more reliably.
Hunt for opportunities to refactor skills to use leading words. A triad spelled out at three sites (**duplication**), a description spending a sentence to gesture at one idea — each is a passage begging to **collapse** into a single token. Examples include:
- "fast, deterministic, low-overhead" -> _tight_ — one quality restated across a phase — into a single pretrained word (a _tight_ loop).
- "a loop you believe in" -> _red_ — converts a fuzzy gate into a binary observable state (the loop goes _red_ on the bug, or it doesn't).
You win twice over: fewer tokens, _and_ a sharper hook for the agent to hang its thinking on. Assume every skill is carrying restatements that leading words retire — go find them.
## Failure modes
Use these to diagnose issues the user may be having with the skill.
- **Premature completion** — ending a step before it's genuinely done, attention slipping to _being done_. Defence, in order: sharpen the completion criterion first (cheap, local); only if it is irreducibly fuzzy _and_ you observe the rush, hide the post-completion steps by splitting (the sequence cut).
- **Duplication** — the same meaning in more than one place. Costs maintenance and tokens, and inflates a meaning's prominence on the ladder past its real rank.
- **Sediment** — stale layers that settle because adding feels safe and removing feels risky. The default fate of any skill without a pruning discipline.
- **Sprawl** — a skill simply too long, even when every line is live and unique. Hurts readability and maintainability and wastes tokens. The cure is the ladder: disclose **reference** behind pointers, and split by **branch** or sequence so each path carries only what it needs.
- **No-op** — a line the model already obeys by default, so you pay load to say nothing. The test: does it change behaviour versus the default? A weak leading word (_be thorough_ when the agent is already thorough-ish) is a no-op; the fix is a stronger word (_relentless_), not a different technique.
- **Negation** — steering by prohibition backfires: _don't think of an elephant_ names the elephant and makes it more available, not less. Prompt the **positive** — state the target behaviour so the banned one is never spoken; keep a prohibition only as a hard guardrail you can't phrase positively, and even then pair it with what to do instead.

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@ -1,79 +0,0 @@
---
name: writing-shape
description: Writing, exploit — shape raw material into an article, paragraph by paragraph.
disable-model-invocation: true
---
<what-to-do>
The user has passed (or will pass) a markdown file of raw material. Treat it as the input pile — anything from a tidy list of fragments to a wall of unstructured prose to a transcript. The format does not matter. Read it end-to-end before doing anything else.
Then run a shaping session that produces a separate article document. This is **exploit**: the exploring is done, the pile is fixed — commit to a structure and mine the pile to fill it. Do not edit the raw material file — it is read-only to this skill.
If the user did not say where to save the article, ask once and remember the path.
</what-to-do>
<supporting-info>
## The loop
1. **Read the pile.** Read the input file in full. Form a sense of what's in it.
2. **Establish the prerequisites.** Settle with the user what the reader knows walking in — the concepts that are **grounded** from the start. Everything else must be grounded by a block before a later block can lean on it. See [Grounding](#grounding).
3. **Draft 23 candidate openings.** Each opening should imply a different thesis or angle for the article. Show all of them. Force the user to pick or compose a hybrid. The chosen opening defines what the rest of the article must do.
4. **Grow paragraph by paragraph.** After the opening lands, ask "given this opening, what does the reader need to hear next?" Pull material from the pile to answer. The next block may only lean on grounded concepts, and grounds new ones as it lands. Argue about the form the next block takes — a paragraph, a list, a table, a callout, a quote, a code block. Each format choice should be deliberate and defensible.
5. **Append to the article file as you go.** Don't batch. Write each agreed paragraph or block immediately so the user can see the article taking shape.
6. **Loop step 4 until the article is done.** The user decides when it's done.
## Grounding
Every **concept** has to be **grounded** before a block can lean on it: the reader either walked in knowing it or met it in an earlier block. A block that reaches for an ungrounded concept loses the reader. The unit is the concept, not the word for it — a block can lean on an idea the reader lacks even with no jargon in sight. Where a concept has a name — a **term** — grounding it means landing the idea and the term together.
A concept gets grounded one of two ways:
- **Prerequisite** — grounded before the opening. The reader brings it. Fixed at the start.
- **Introduced** — a block establishes it, and from then on it's grounded for the rest of the article.
Keep a running list of what's grounded. When you ask "what does the reader need to hear next?", an ungrounded concept the next move needs is itself the answer: ground it first — here or in an earlier block — or you can't make the move. This is the gap-naming of [Pulling from the pile](#pulling-from-the-pile) one level up: there the pile is missing material; here the article is missing a foundation.
The lever is what you make a prerequisite versus what you ground inside the article. Demand too much up front and you shut readers out; ground too much inside and the opening drowns in definitions. Settle it with the user when you establish prerequisites.
## Conversational feel
This is a grilling session inverted. In ideation, the question was "what are you actually noticing?" Here it's "what is this article actually arguing, and in what order does the reader need to hear it?" Push back. Refuse to let weak transitions slide. If a paragraph doesn't earn its place, cut it.
Specific moves to keep using:
- "What does this paragraph do for the reader that the previous one didn't?"
- "If I cut this, what breaks?"
- "Is this prose, or should it be a list? Why prose?"
- "This sentence is doing two jobs — split it or pick one."
- "The opening promised X. We've drifted to Y. Either re-thread it or change the opening."
## Pulling from the pile
Treat the raw material as a quarry, not a script. Pull a fragment, rework it to fit the surrounding paragraph, and place it. A fragment may be split across multiple paragraphs, merged with another, or paraphrased. The pile's job is to be mined; the article's job is to read as one voice.
If the pile lacks something the article needs, name the gap explicitly: "We need an example here and the pile doesn't have one — give me one now or we cut this section."
## Format arguments to actually have
When choosing how to render a block, weigh these tradeoffs out loud with the user, not silently:
- **Prose vs. list.** Prose carries argument; lists carry parallel items. If items aren't truly parallel, prose is better. If they are, a list is faster to scan.
- **Inline vs. callout.** Tips, warnings, and asides go in callouts (`> [!TIP]`, `> [!NOTE]`) — but only if they'd genuinely derail the main argument inline. Otherwise leave them inline.
- **Table vs. repeated structure.** If the same shape repeats 3+ times with the same fields, a table. Otherwise prose with bold leads.
- **Quote vs. paraphrase.** Quote when the original wording is the point. Paraphrase when only the idea matters.
- **Code block vs. inline code.** Multi-line, runnable, or illustrative → block. Single token or identifier → inline.
## Writing rhythm
Append to the article file as each block is agreed. Re-read the file from disk before every write — the user may have edited between turns. Never overwrite blindly. If the user wants a paragraph rewritten, edit that specific paragraph in place; leave the rest alone.
## Out of scope
- Mining for new fragments that aren't in the pile (handle gaps as in "Pulling from the pile").
- Editing the raw material file.
- Publishing, formatting for a specific platform, or adding frontmatter the user didn't ask for.
</supporting-info>

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@ -52,7 +52,13 @@ jobs:
- name: Run unit tests
shell: bash
run: |
python -m pytest tests/unit/ \
python -m pytest tests/ \
--ignore=tests/sandbox \
--ignore=tests/cli \
--ignore=tests/e2e \
--ignore=tests/journey \
--ignore=tests/chaos \
--ignore=tests/audit \
-v --tb=short --timeout=60
# ---------------------------------------------------------------------------

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@ -18,23 +18,11 @@ jobs:
with:
python-version: '3.11'
- uses: actions/setup-node@v4
with:
node-version: 20
cache: "npm"
cache-dependency-path: paperforge/plugin/package-lock.json
- name: Build Python package
- name: Build package
run: |
python -m pip install --upgrade build
python -m build
- name: Build plugin bundle
working-directory: paperforge/plugin
run: |
npm ci
npm run build
- name: Publish to PyPI
uses: pypa/gh-action-pypi-publish@release/v1
with:

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@ -31,10 +31,6 @@ jobs:
npm ci
npx vitest run --reporter=verbose
- name: Build plugin bundle
working-directory: paperforge/plugin
run: npm run build
- name: Create Release
uses: softprops/action-gh-release@v2
with:

20
.gitignore vendored
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@ -38,23 +38,3 @@ Thumbs.db
.vite/
paperforge/plugin/node_modules/
# Temp files
.opencode/tmp/
.ai-bridge/
# Audit per-paper artifacts (keep root-level summary files)
audit/*/
!audit/*.json
!audit/*.md
# Temp / generated files
.git-rewrite/
.tmp/
local-*.md
loss_*.md
audit/tmp_pdf/
audit/media_asset_samples/
# OpenCode MCP binaries
.opencode/mcp/

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@ -1 +0,0 @@
cd paperforge/plugin && npx lint-staged && npm run typecheck && npm run test

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@ -1,34 +0,0 @@
# PaperForge — Project Record Management
Project state is split across three layers with distinct roles:
- **Narrative ledger** (`PROJECT-MANAGEMENT.md`) — full history, updated every session end
- **Active queue** (`project/current/ocr-v2-active-queue.md`) — next-work priorities, updated at milestones
- **Archive** (`project/archive/`) — superseded files from `current/`, moved not deleted
## Update Rules
### PROJECT-MANAGEMENT.md — Every Session End
Update before final commit. Touches:
- Executive summary (§0) — one-line current state + next action
- Current status (§2) — test counts, component state, fix table
- Remaining issues (§3) — resolved out, new ones in
- Active queue checkpoint (§4) — next steps
- Decision log (§6) — one line per decision with rationale
- Session timeline (§8) — compressed one-line record
### project/current/ — Milestones Only
`ocr-v2-active-queue.md` updates after major fix series or priority shifts. Never mid-session.
Other `ocr-v2-*.md` files: update only when architecture or evidence changes.
### project/archive/ — Move, Don't Delete
When a current file no longer reflects active truth: prepend archive header (date + reason + replacement), move to `project/archive/`, remove from `current/`.
## Format Conventions
- **Timeline entry** (§8): `| YYYY-MM-DD | Short title | Key results — what was done, what was found | §N.M |`
- **Decision log** (§6): `| YYYY-MM-DD | Decision title | Rationale — why, not what |`
- **Fix table** (§2.3): `| # | Paper + symptom | Root cause | Fix approach | Commit |`

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@ -1,11 +0,0 @@
# Matt Workflow Guardrails
- Ask Matt owns the engineering lifecycle: route with `/ask-matt`, implement one agent-ready issue with `/implement`, then run `/review`. Do not introduce a second orchestration workflow.
- One implementation session handles one issue in one authoritative worktree. Start a fresh session before changing issues; use `/handoff` only when context must cross sessions.
- Before editing, pin the issue, parent PRD, issue `updated_at`, base SHA, worktree root, scope, acceptance criteria, and verification commands. If the issue changes, stop and refresh this contract.
- Use one writer. Parallel `task` batches may contain only read-only `scout`, `reviewer`, or `librarian` agents. Never let parallel agents edit shared files or the same worktree.
- Never copy implementation files between the main checkout and a worktree. All reads, writes, tests, reviews, and commits for an issue use its authoritative worktree.
- Follow Matt `/tdd` at pre-agreed seams. Run focused checks while implementing and the issue-specific final gate once after the last mutation; UI work also needs a real-browser smoke test.
- Review exactly once on Matt's two axes. Consolidate findings into one repair pass and one re-review. If an important defect remains, return to the acceptance contract or split the issue; do not create repeated Final/Definitive review loops.
- Commit, merge, push, create/merge a PR, or close an issue only after verification succeeds after the last mutation. Update `PROJECT-MANAGEMENT.md` and the active queue according to project rules before closeout.
- The removed Superpowers workflows are not part of this project. Do not reinstall, invoke, emulate, or delegate through them.

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@ -1,59 +0,0 @@
# Advisor policy — sparse, risk-focused review
Your job is not to optimize, polish, or co-design.
Your job is to prevent expensive mistakes.
Default to silence.
Only speak when one of these is true:
1. The agent is about to do something dangerous, irreversible, or likely to damage user work, data, or repo state.
2. The agent is making a design decision that is clearly brittle, unstable, or likely to cause incorrect behavior, hidden coupling, or expensive rework.
3. The agent is operating on a false assumption that will likely invalidate the current line of work.
4. The agent is about to miss a hard constraint that materially changes correctness.
Priorities:
- Dangerous actions
- Data loss or destructive operations
- Broken or fragile architecture
- Incorrect assumptions with high downstream cost
- Real correctness risks
De-prioritize or ignore:
- Style suggestions
- Naming improvements
- Small refactors
- "Could be cleaner" comments
- Alternative designs unless the current one is materially risky
- Minor optimizations
- General best-practice commentary
Severity policy:
- Use `blocker` only for clear stop-now situations.
- Use `concern` only for high-confidence, high-cost risks.
- Avoid `nit` unless the note prevents future confusion at near-zero token cost.
- When in doubt, do not advise.
Token discipline:
- Prefer no message over a low-value message.
- Never restate what the agent already knows.
- Never give a suggestion unless the expected benefit clearly exceeds the token cost.
- Keep advice extremely short, concrete, and decision-oriented.
Design review stance:
- Allow local freedom when the design is reasonable.
- Intervene only when the design is not robust enough for likely real use.
- Do not push ideal architecture over adequate architecture unless the current path is likely to fail.
One-message rule:
- If multiple issues exist, report only the highest-severity, highest-leverage one.
- Do not stack minor concerns.
Additional strictness:
- Treat absence of advice as the normal outcome.
- Do not emit advice for speculative risks.
- Do not emit advice for possible-improvement comments.
- Only intervene when the risk is concrete enough that a careful reviewer would be surprised if nothing were said.
Reminder:
Silence is success. Speak only when the agent is likely to make a costly mistake.

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@ -1,10 +0,0 @@
memory:
backend: mnemopi
mnemopi:
scoping: per-project
advisor:
enabled: true
subagents: false
syncBacklog: off
immuneTurns: 8

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@ -1,90 +0,0 @@
import { execFileSync } from "node:child_process";
import path from "node:path";
import { describe, expect, test } from "bun:test";
import register from "./matt-guard";
type Handler = (
event: Record<string, unknown>,
context?: { cwd: string },
) => unknown | Promise<unknown>;
const root = path.resolve(import.meta.dir, "../../..");
function handlers() {
const registered: Record<string, Handler> = {};
register({
on: (event: string, handler: Handler) => {
registered[event] = handler;
},
} as unknown as Parameters<typeof register>[0]);
return registered;
}
function foreignWorktree(): string | undefined {
const current = path.normalize(root).toLowerCase();
return execFileSync("git", ["worktree", "list", "--porcelain"], {
cwd: root,
encoding: "utf8",
})
.split(/\r?\n/)
.filter((line) => line.startsWith("worktree "))
.map((line) => path.normalize(line.slice("worktree ".length)))
.find((worktree) => worktree.toLowerCase() !== current);
}
describe("Matt workflow guard", () => {
test("allows parallel read-only agents and blocks a writer", async () => {
const hook = handlers();
const context = { cwd: root };
expect(
await hook.tool_call(
{
toolName: "task",
input: { tasks: [{ agent: "reviewer" }, { agent: "scout" }] },
},
context,
),
).toBeUndefined();
expect(
await hook.tool_call(
{
toolName: "task",
input: { tasks: [{ agent: "reviewer" }, {}] },
},
context,
),
).toMatchObject({ block: true });
});
test("requires verification after the latest mutation", async () => {
const hook = handlers();
const context = { cwd: root };
const commit = { toolName: "bash", input: { command: "git commit --dry-run" } };
expect(await hook.tool_call(commit, context)).toMatchObject({ block: true });
await hook.tool_result({
toolName: "bash",
input: { command: "npm test" },
isError: false,
details: { exitCode: 0 },
});
expect(await hook.tool_call(commit, context)).toBeUndefined();
await hook.tool_call({ toolName: "edit", input: "mutation" }, context);
expect(await hook.tool_call(commit, context)).toMatchObject({ block: true });
});
test.skipIf(!foreignWorktree())("blocks writes into another linked worktree", async () => {
const hook = handlers();
const target = path.join(foreignWorktree()!, "CONTEXT.md");
expect(
await hook.tool_call(
{ toolName: "write", input: { path: target } },
{ cwd: root },
),
).toMatchObject({ block: true });
});
});

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@ -1,211 +0,0 @@
import { execFileSync } from "node:child_process";
import path from "node:path";
import type { ExtensionAPI } from "@oh-my-pi/pi-coding-agent";
const READ_ONLY_AGENTS: Record<string, true> = {
scout: true,
reviewer: true,
librarian: true,
};
const RELEASE_COMMAND =
/\bgit(?:\.exe)?\b[^\r\n;&|]*\b(?:commit|merge|push)\b|\bgh(?:\.exe)?\s+(?:issue\s+close|pr\s+(?:create|merge))\b/i;
const VERIFICATION_COMMAND =
/\b(?:pytest|unittest|vitest|jest|ruff|mypy|pyright|tsc)\b|\b(?:npm|pnpm|yarn|bun)\s+(?:test|run\s+(?:test|typecheck|build|lint))\b|\bcargo\s+(?:test|check)\b|\bgo\s+test\b|\bdotnet\s+test\b/i;
const URI = /^[a-z][a-z0-9+.-]*:\/\//i;
interface GuardState {
verifiedAfterMutation: boolean;
}
function record(value: unknown): Record<string, unknown> {
return value && typeof value === "object"
? (value as Record<string, unknown>)
: {};
}
function json(value: unknown): Record<string, unknown> {
try {
return record(JSON.parse(String(value ?? "")));
} catch {
return {};
}
}
function runGit(cwd: string, args: string[]): string {
try {
return execFileSync("git", args, {
cwd,
encoding: "utf8",
windowsHide: true,
stdio: ["ignore", "pipe", "ignore"],
}).trim();
} catch {
return "";
}
}
function normalized(value: string): string {
const resolved = path.resolve(value);
return process.platform === "win32" ? resolved.toLowerCase() : resolved;
}
function isWithin(root: string, candidate: string): boolean {
const relative = path.relative(root, candidate);
return relative === "" || (!relative.startsWith("..") && !path.isAbsolute(relative));
}
function crossesWorktrees(candidate: string, cwd: string): boolean {
if (!candidate || URI.test(candidate)) return false;
const current = runGit(cwd, ["rev-parse", "--show-toplevel"]);
if (!current) return false;
const target = normalized(path.resolve(cwd, candidate));
const currentRoot = normalized(current);
const worktrees = runGit(cwd, ["worktree", "list", "--porcelain"])
.split(/\r?\n/)
.filter((line) => line.startsWith("worktree "))
.map((line) => normalized(line.slice("worktree ".length)));
return worktrees.some(
(root) => root !== currentRoot && isWithin(root, target),
);
}
function pathsFromCall(toolName: string, input: unknown): string[] {
const fields = record(input);
if (toolName === "edit") {
const patch = typeof input === "string" ? input : String(fields.input ?? "");
return [...patch.matchAll(/^\[([^#\r\n]+)#[0-9A-F]{4}\]$/gm)].map(
(match) => match[1],
);
}
if (toolName === "ast_edit") {
return Array.isArray(fields.paths) ? fields.paths.map(String) : [];
}
if (toolName === "lsp") {
return typeof fields.file === "string" ? [fields.file] : [];
}
if (toolName !== "write") return [];
const target = String(fields.path ?? "");
if (target === "xd://ast_edit") {
const payload = json(fields.content);
return Array.isArray(payload.paths) ? payload.paths.map(String) : [];
}
if (target === "xd://lsp") {
const payload = json(fields.content);
return typeof payload.file === "string" ? [payload.file] : [];
}
return URI.test(target) ? [] : [target];
}
function tasksFromCall(input: unknown): Record<string, unknown>[] {
const tasks = record(input).tasks;
return Array.isArray(tasks) ? tasks.map(record) : [];
}
function hasWriterTask(input: unknown): boolean {
return tasksFromCall(input).some(
(task) => READ_ONLY_AGENTS[String(task.agent ?? "")] !== true,
);
}
function isMutatingCall(toolName: string, input: unknown): boolean {
if (toolName === "edit" || toolName === "ast_edit") return true;
if (toolName === "task") return hasWriterTask(input);
if (toolName === "lsp") {
const fields = record(input);
return (
fields.action === "rename" ||
fields.action === "rename_file" ||
(fields.action === "code_actions" && fields.apply === true)
);
}
if (toolName !== "write") return false;
const fields = record(input);
const target = String(fields.path ?? "");
if (!URI.test(target)) return true;
if (target === "xd://ast_edit") return true;
if (target !== "xd://lsp") return false;
const payload = json(fields.content);
return (
payload.action === "rename" ||
payload.action === "rename_file" ||
(payload.action === "code_actions" && payload.apply === true)
);
}
function releaseAction(toolName: string, input: unknown): boolean {
const fields = record(input);
if (toolName === "bash") return RELEASE_COMMAND.test(String(fields.command ?? ""));
if (toolName === "github") {
return ["pr_create", "pr_push"].includes(String(fields.op ?? ""));
}
if (toolName !== "write" || fields.path !== "xd://github") return false;
return ["pr_create", "pr_push"].includes(String(json(fields.content).op ?? ""));
}
function successfulVerification(event: Record<string, unknown>): boolean {
if (event.toolName !== "bash" || event.isError === true) return false;
const input = record(event.input);
if (!VERIFICATION_COMMAND.test(String(input.command ?? ""))) return false;
const details = record(event.details);
const exitCode = details.exitCode ?? details.exit_code ?? details.code;
if (typeof exitCode === "number") return exitCode === 0;
const content = Array.isArray(event.content) ? event.content : [];
const text = content.map((chunk) => String(record(chunk).text ?? "")).join("\n");
return !/command exited with code\s+[1-9]\d*/i.test(text);
}
export default function mattGuard(pi: ExtensionAPI): void {
const state: GuardState = { verifiedAfterMutation: false };
pi.on("tool_call", async (event, ctx) => {
const toolName = String(event.toolName);
const input = event.input;
if (toolName === "task") {
const tasks = tasksFromCall(input);
if (tasks.length > 1 && hasWriterTask(input)) {
return {
block: true,
reason:
"Matt guard: parallel task batches may contain only scout, reviewer, or librarian agents. Use one writer.",
};
}
}
const crossWorktree = pathsFromCall(toolName, input).find((candidate) =>
crossesWorktrees(candidate, ctx.cwd),
);
if (crossWorktree) {
return {
block: true,
reason: `Matt guard: refusing write into another Git worktree: ${crossWorktree}`,
};
}
if (releaseAction(toolName, input) && !state.verifiedAfterMutation) {
return {
block: true,
reason:
"Matt guard: run the issue-specific verification gate after the last mutation before commit, merge, push, PR creation, or issue close.",
};
}
if (isMutatingCall(toolName, input)) state.verifiedAfterMutation = false;
});
pi.on("tool_result", async (event) => {
if (successfulVerification(event as unknown as Record<string, unknown>)) {
state.verifiedAfterMutation = true;
}
});
}

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@ -1,9 +0,0 @@
{
"$schema": "https://opencode.ai/config.json",
"skills": {
"paths": [
".opencode/skills",
"C:/Users/Lin/ponytail/skills"
]
}
}

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@ -1,100 +0,0 @@
---
name: paperforge-development
description: Use when doing PaperForge engineering or internal OCR truth-audit work. Triggered by: "OCR审计" "审OCR" "审计OCR" "审一下" "审计这篇" "block review" "ocr truth audit" "annotated pages" "看下角色对不对" "块角色" "visual audit" "对照一下图片" "校对block".
---
# PaperForge Development
Developer-only skill family for internal PaperForge OCR audit work.
Use this when the task is to inspect OCR truth, classify failures, and write audit evidence without changing the runtime PaperForge skill graph.
## Route
- OCR truth audit: `workflows/ocr-truth-audit.md`
## Scripts
- `scripts/ocr_truth_audit.py` — artifact generator (annotated pages, summaries, findings)
- `scripts/audit_helpers.py` — structured data maps for vision agents (figure, frontmatter, reference, body)
- `scripts/verify_review_coverage.py` — coverage verification
- `scripts/diff_audit.py` — diff audit between truth and pipeline
## Invariant
- Truth first.
- Do not start by authoring expectations.
- Establish block-level truth from page visuals and artifacts before comparing pipeline behavior.
## Agent Dispatch Rules (CRITICAL — read before any audit task)
The #1 source of audit errors is using the wrong tool for the question.
Follow these rules unconditionally:
### When to dispatch `vision` subagent (MUST):
The workflow in `workflows/ocr-truth-audit.md` Step 6 tells you the exact commands.
Summary:
| Audit domain | Data recipe | Vision template |
|-------------|-------------|----------------|
| Figures | `audit_helpers.py --recipe figure_map` | atoms/ocr-vision-audit-templates.md — Template 1 |
| Frontmatter | `audit_helpers.py --recipe frontmatter_map` | Template 2 |
| References | `audit_helpers.py --recipe reference_map` | Template 3 |
| Body text | `audit_helpers.py --recipe body_text_map` | Template 4 |
**Procedure:** (1) Run the recipe → get JSON. (2) Read the template. (3) Paste JSON into template. (4) Dispatch as `vision` subagent prompt.
### Forbidden agent patterns:
- `general` subagent claiming to "see" an annotated page. **Only `vision` can view images.**
- Concluding figure matching from `figure_table_ownership_summary.json` alone. **Must cross-check with source `figure_inventory.json` AND visual truth.**
- Reporting `reference_intrusion_candidates` as errors without checking block roles.**noise blocks in `reference_zone` are expected.**
- "The block has 0 candidates so figure is on another page" without scanning `page_{N-1}_index.json` and `page_{N+1}_index.json`.
### Finding trust boundaries (CRITICAL):
The auto-generated findings in `audit_report.json` contain substantial noise.
**Only these [CODE] checks are reliable — all others need [VISION]:**
| Finding category | Trust? | Why |
|-----------------|--------|-----|
| `role_mismatch` (from diff_audit.py) | ✅ [CODE] | Direct string comparison, 100% |
| `zone_mismatch` (from block_review.jsonl) | ✅ [CODE] | Direct string comparison, 100% |
| `render_mapping_error` — non-noise blocks | ✅ [CODE] | Substring match, exclude noise |
| `unmatched_asset_count > 0` | ✅ [CODE] | deterministic count from inventory |
| `coverage_check status` | ✅ [CODE] | direct comparison |
| `reference_span_audit status` | ✅ [CODE] | deterministic |
| `same_page_boundary_error` | ❌ NEVER | Page-level heuristic, no actionable info |
| `reference_span_error` (audit_report.json) | ⚠️ Partially | Span may be too wide; need vision to verify boundary |
| `object_ownership_error` (audit_report.json) | ❌ NEVER | Misses unmatched assets entirely |
| `render_mapping_error` — noise blocks | ❌ NEVER | noise should not be in fulltext |
| `image_quality`, `font`, `color`, `typography` | ❌ [VISION] only | No metadata available |
### Per-role audit strategies:
Full methodology for each of the 28 canonical roles is in `atoms/ocr-role-audit-strategies.md`.
Each role is classified into one of 4 tiers:
| Tier | Method | Roles |
|------|--------|-------|
| A | Vision-required | `figure_asset`, `media_asset`, `figure_caption`, `figure_caption_candidate`, `table_caption`, `table_asset`, `table_html`, `structured_insert` |
| B | Data-primary, vision-confirm | `body_paragraph`, `section_heading`, `subsection_heading`, `reference_item`, `reference_heading`, `backmatter_heading`, `backmatter_body` |
| C | Data-sufficient | `paper_title`, `authors`, `affiliation`, `abstract_heading`, `abstract_body`, `keywords`, `frontmatter_support`, `frontmatter_noise`, `footnote` |
| D | Structural-only | `tail_candidate_body`, `backmatter_boundary_*`, `ocr_raw_error`, `unknown_structural`, `page_header`, `page_footer`, `noise` |
### Deep per-role + quality audit:
**`atoms/ocr-vision-audit-master.md`** extends all 4 templates with:
- Per-role analysis covering role/zone/reference AND quality (typography, image, table)
- Cross-reference pathways linking all audit data sources for any block_id
- Chart-type routing to `paperforge/skills/paperforge/atoms/chart-reading/*.md`
- Full-page typography sweep (font consistency, alignment, orphans/widows, heading hierarchy)
- Output format for block_review.jsonl with optional `quality_checks` and `page_typography` fields
After the 4 recipe-driven vision passes in Step 6, run the master atom:
```bash
# Read the master atom before dispatching per-role vision
cat .opencode/skills/paperforge-development/atoms/ocr-vision-audit-master.md
```
It contains the per-role data-cross-ref + quality-check methodology. Paste the relevant section into each vision subagent prompt depending on which role set the agent is reviewing.

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@ -1,131 +0,0 @@
# OCR Audit Report Schema
Truth-first invariant:
- Do not start by authoring expectations.
- Determine truth from page visuals and artifacts first.
- Use reports to record truth and mismatches, not to normalize incorrect output.
External vault invariant:
- The OCR source root is outside the repo.
- The audit helper must not assume a repo-local literature vault.
- The caller must provide `--source-root` or set `PAPERFORGE_OCR_ROOT`.
## Required Output Files
Write outputs under `audit/<paper_key>/`.
Concrete example:
- `audit/CAQNW9Q2/audit_report.md`
- `audit/CAQNW9Q2/audit_report.json`
- `audit/CAQNW9Q2/audit_scope.json`
- `audit/CAQNW9Q2/block_review.jsonl`
- `audit/CAQNW9Q2/coverage_check.json`
- `audit/CAQNW9Q2/block_coverage_summary.json`
- `audit/CAQNW9Q2/page_risk_summary.json`
- `audit/CAQNW9Q2/reference_intrusion_candidates.json`
- `audit/CAQNW9Q2/figure_table_ownership_summary.json`
- `audit/CAQNW9Q2/fulltext_block_mapping_summary.json`
- `audit/CAQNW9Q2/reference_span_audit.json`
- `audit/CAQNW9Q2/annotated_pages/page_*_overview.png` — all-block overview with short numeric labels
- `audit/CAQNW9Q2/annotated_pages/page_*_index.json` — per-page block-to-metadata mapping
## Primary Categories
- `frontmatter_error`
- `body_flow_error`
- `reference_span_error`
- `same_page_boundary_error`
- `backmatter_error`
- `object_ownership_error`
- `reading_order_error`
- `render_mapping_error`
## Meta Category
- `audit_truth_gap`
Use `audit_truth_gap` when the audit process fails to surface real block-level truth or when prior expectations drift away from visual truth.
## Severities
- `critical`
- `major`
- `minor`
- `cosmetic`
Severity tracks trust and downstream damage, not implementation effort.
## audit_report.json Example
```json
{
"paper_key": "CAQNW9Q2",
"mode": "high-risk",
"artifact_fingerprint": {
"result_json_hash": "...",
"structured_blocks_hash": "...",
"fulltext_hash": "...",
"document_structure_hash": "..."
},
"reviewed_pages": [1, 7, 8],
"reviewed_blocks": ["p1:b3", "p7:b12"],
"findings": [
{
"category": "reference_span_error",
"severity": "critical",
"block_ids": ["p7:b12"],
"truth": "block belongs outside reference span",
"pipeline_behavior": "rendered inside accepted references",
"root_cause_hypothesis": "same-page boundary inference overreach",
"evidence": {
"annotated_page": "annotated_pages/page_007.png",
"artifact": "structure/document_structure.json"
}
}
]
}
```
## reference_span_audit.json Example
```json
{
"reference_span": {
"status": "ACCEPT",
"span_id": "refspan_001",
"start": {
"page": 7,
"column": 1,
"y": 1032,
"block_id": "p7:b12"
},
"end": {
"page": 10,
"column": 2,
"y": 1398,
"block_id": "p10:b48"
},
"ordered_block_ids": ["p7:b12", "p7:b13"],
"inside_block_ids": ["p7:b12", "p7:b13"],
"explicitly_outside_nearby_block_ids": ["p7:b10", "p7:b11"],
"intrusion_candidates": []
}
}
```
## Minimum Reporting Expectations
- `audit_report.md` summarizes reviewed scope, freshness status, findings, and repair vs residual recommendations.
- `audit_report.json` is the machine-readable source of findings.
- `audit_scope.json` defines which pages and blocks must be reviewed for the chosen mode.
- `block_review.jsonl` is the agent-written visual truth review log.
- `coverage_check.json` is written by `verify_review_coverage.py` and must fail when mandatory reviews are missing.
- `block_coverage_summary.json` tracks which blocks were reviewed and their review state.
- `page_risk_summary.json` records page scores and reasons.
- `reference_intrusion_candidates.json` records candidate reference contamination.
- `figure_table_ownership_summary.json` records caption/asset/object mismatches.
- `fulltext_block_mapping_summary.json` records source-to-render placement checks.
- `reference_span_audit.json` records accepted reference span boundaries and intrusion checks.

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# OCR Canonical Roles
`truth_role` in `block_review.jsonl` MUST be one of these canonical pipeline roles.
Do not invent new role names — use only the set below. Non-canonical names
will be normalized by `diff_audit.py` but relying on that is a workflow violation.
## Frontmatter
| Role | When |
|------|------|
| `paper_title` | Document title on page 1 |
| `authors` | Author byline |
| `affiliation` | Author affiliation block |
| `frontmatter_support` | Correspondence, DOI, dates, data availability |
| `frontmatter_noise` | Page-1 non-structural furniture (journal name, article type, publisher strip) |
| `abstract_heading` | "Abstract" label |
| `abstract_body` | Abstract body text |
| `keywords` | Keywords block |
## Body
| Role | When |
|------|------|
| `section_heading` | Top-level section heading |
| `subsection_heading` | Second-level section heading |
| `sub_subsection_heading` | Third-level section heading |
| `body_paragraph` | Narrative body paragraph |
| `tail_candidate_body` | Body paragraph in the tail spread |
## Reference
| Role | When |
|------|------|
| `reference_heading` | "References" heading |
| `reference_item` | Individual reference entry |
## Backmatter
| Role | When |
|------|------|
| `backmatter_heading` | Backmatter section heading (Acknowledgments, Funding, etc.) |
| `backmatter_heading_candidate` | Possible backmatter heading, not yet confirmed |
| `backmatter_body` | Backmatter body paragraph |
| `backmatter_boundary_heading` | Confirmed backmatter boundary heading |
| `backmatter_boundary_candidate` | Possible backmatter boundary |
## Figure / Table
| Role | When |
|------|------|
| `figure_asset` | Figure image/media |
| `figure_caption` | Confirmed figure caption |
| `figure_caption_candidate` | Probable figure caption, not fully confirmed |
| `figure_inner_text` | Text inside a figure (panel labels, axis labels) |
| `table_caption` | Confirmed table caption |
| `table_caption_candidate` | Probable table caption, not fully confirmed |
| `table_asset` | Table image |
| `table_html` | HTML native table |
| `table_html_candidate` | Probable HTML native table |
| `media_asset` | Generic media image (when figure/table type is unclear) |
## Structural Inserts
| Role | When |
|------|------|
| `structured_insert` | Structured block (callout box, highlight, algorithm) |
| `structured_insert_candidate` | Probable structured insert |
| `non_body_insert` | Non-body decorative insert (publisher strip, sidebar filler) |
## Noise & Fallback
| Role | When |
|------|------|
| `noise` | Decorative line, page furniture, garbage OCR |
| `footnote` | Page footnote |
| `unknown_structural` | Block exists but no role fits (structural gate fallback) |
| `ocr_raw_error` | OCR extraction failure (empty text) |
| `page_header` | Running header repeat |
| `page_footer` | Running footer repeat |
## Ground Truth Only (seed roles, never final)
These are assigned as `seed_role` by the early role assignment but never appear
as the final pipeline output role. When auditing, use the final role above
even if the seed role seems more intuitive:
- `figure_title` (raw OCR label, not a final role)

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# OCR Page Risk Scoring
Use this only for `high-risk` mode page selection.
Truth-first note:
- The score prioritizes likely inspection value.
- It does not author expected truth.
- Final judgment still comes from visual review plus artifact grounding.
## Fixed Additive Formula
```text
page_risk_score =
+5 if page == 1
+5 if contains reference_heading
+4 if contains both body_paragraph and reference_item
+4 if contains tail/body/ref mixed evidence
+4 if figure/table asset count >= 2
+3 if caption count != asset count
+3 if reader/object coverage gap exists
+2 if verify-required HOLD count >= threshold
+2 if unknown_structural count >= threshold
```
## Risk Reason Hints
Suggested reason labels:
- `frontmatter_page`
- `reference_heading_present`
- `mixed_body_reference`
- `same_page_boundary`
- `multi_asset_page`
- `caption_asset_mismatch`
- `reader_object_gap`
- `hold_threshold`
- `unknown_structural_threshold`
## Example Output Shape
```json
{
"page": 7,
"risk_score": 14,
"risk_reasons": [
"mixed_body_reference",
"reference_heading_present",
"same_page_boundary"
],
"recommended_audit_targets": [
"reference_span",
"reading_order"
]
}
```

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# OCR Per-Role Audit Strategies
> **Use this as a quick reference** for deciding how to inspect any role.
> For actual audit work, use `scripts/audit_helpers.py` recipes + `ocr-vision-audit-templates.md`.
> Do NOT write custom Python for per-role checks — it's already built.
## Tier Classification
| Tier | Method | When |
|------|--------|------|
| A | **Vision-required** | Must dispatch `vision` subagent. Data alone insufficient. |
| B | **Data-primary, vision-confirm** | Read data first. Dispatch vision only when data flags an issue. |
| C | **Data-sufficient** | JSON analysis is enough. Vision only for ordering/layout ambiguity. |
| D | **Structural-only** | Read from block trace / document structure. No vision needed. |
## Role → Tier Mapping
### Tier A — Vision-Required
| Role | Why vision is needed |
|------|---------------------|
| `figure_asset` | Is the box covering an actual image? Are sub-panels merged? |
| `media_asset` | Is this a figure, a table, or a phantom block? |
| `figure_caption` | Is it a real caption, sub-panel label, or body mention? Where is its image? |
| `figure_caption_candidate` | Should it be confirmed or demoted? |
| `figure_inner_text` | Is it inside a figure (panel label) or separate text? |
| `table_caption` | Same as figure_caption. Cross-page? |
| `table_caption_candidate` | Should it be confirmed? |
| `table_asset` | Is this actually a table image? |
| `table_html` | Is the HTML table rendering correctly? |
| `structured_insert` | Is this a callout box or mislabeled body text? |
| `structured_insert_candidate` | Should it be confirmed? |
| `non_body_insert` | What is this element visually? |
### Tier B — Data-Primary, Vision-Confirm
| Role | Data check | When to add vision |
|------|-----------|-------------------|
| `body_paragraph` | zone=body_zone? text non-empty? | zone wrong, text empty, or two-column ambiguity |
| `section_heading` | numbering depth, heading absorption (two levels in one block) | verify visually if absorption detected |
| `subsection_heading` | same as section_heading | same |
| `sub_subsection_heading` | same | same |
| `reference_heading` | in reference_zone? before first reference_item? | transition page boundary |
| `reference_item` | in reference_zone? correct numbering pattern? | real intrusions or numbering gaps |
| `backmatter_heading` | after last reference? in backmatter_zone? | if inside reference_zone |
| `backmatter_body` | same | same |
### Tier C — Data-Sufficient
`paper_title`, `authors`, `affiliation`, `frontmatter_support`, `frontmatter_noise`,
`abstract_heading`, `abstract_body`, `keywords`, `footnote`
These are on page 1 (or page N for footnotes) at known positions with known patterns.
Read `page_001_index.json`. Vision only for ordering ambiguity or badge mislabel suspicion.
### Tier D — Structural-Only
`tail_candidate_body`, `backmatter_boundary_candidate`, `backmatter_boundary_heading`,
`ocr_raw_error`, `unknown_structural`, `page_header`, `page_footer`, `noise`
Read from `blocks.structured.jsonl` (text, span_metadata, _ocr_raw_status) or
`document_structure.json` (tail order, boundaries). No vision needed.
## Common Failure Patterns (quick reference)
| Pattern | Signal in data | Confirmation |
|---------|---------------|-------------|
| Sub-panels not merged | N asset blocks, 1 fig with < N assets | Vision: are they panels of same figure? |
| Caption sandwiched between figs | close_asset_tie with above+below | Vision: which figure owns the caption? |
| Cross-page caption | no_asset_match, prev/next page has orphan assets | Vision: is image on adjacent page? |
| Sub-panel heading as caption | figure_caption with text like "Musculoskeletal conditions..." | Vision: is this a panel heading? |
| Truncated legend as standalone | "Fig. 6" only, long caption below | Vision: composite figure with shared caption? |
| Table mislabeled as figure | media_asset with raw_label=table | Vision: is this a table or figure? |
| Body text as noise | noise with text_preview > 30 chars, not at page edge | Vision: is this body text? |
| Heading absorption | section_heading text has "2. ... 2.1. ..." | Vision: two heading levels merged? |
| Badge as authors | authors text = "HIGHLIGHTED PAPER" | Vision: is it a badge or authors? |
| Reference zone intrusion | body_paragraph in reference_zone | Vision: verify boundary |

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# OCR Vision Audit Master — CODE vs VISION 严格分离
> **原则:** 每个检查标注来源。
> `[CODE]` = 从 JSON 文件或 PDF 元数据精确提取,无需视觉判断。
> `[VISION]` = 必须看 `page_NNN.png`,代码没有所需数据。
>
> 字体属性family、size、weight、color、italic`blocks.structured.jsonl`
> `span_metadata` / `span_signature` 中,代码可直接提取。不要用 vision 做字体检查。
---
## 0. 数据源权限
| 文件 | `[CODE]` 可读 | `[VISION]` 需要 |
|------|-------------|----------------|
| `page_NNN.png` | ❌ | ✅ |
| `page_NNN_index.json` | ✅ role, zone, bbox, text | — |
| `block_coverage_summary.json` | ✅ role, raw_label, zone, bbox | — |
| `blocks.structured.jsonl` (OCR 源) | ✅ **span_metadata (font/color/size), span_signature, style_family** | — |
| `block_review.jsonl` | ✅ truth_role, truth_zone, truth_reference_membership | — |
| `figure_table_ownership_summary.json` | ✅ matched/ambiguous/unmatched 计数 | ⚠️ 验证匹配正确性 |
| `fulltext_block_mapping_summary.json` | ✅ found_in_fulltext排除 noise 后) | — |
| `reference_span_audit.json` | ✅ inside/outside | ⚠️ 边界验证 |
| `coverage_check.json` | ✅ 100% 可靠 | — |
---
## 1. `[CODE]` 自动化可信任检查
以下从 JSON 数据直接提取,**不看图片**,结果决定性的。
### 1.1 Role 一致性 — block_review.jsonl + diff_audit.py
```yaml
输入: block_review.jsonl 的 truth_role vs _current_role
changed_blocks_after_fallback.json
方法: 字符串直接比较
信任度: 100%
输出: 每个 role mismatch 的 {block_id, pipeline_role, truth_role}
```
### 1.2 Zone 一致性 — block_review.jsonl
```yaml
输入: block_review.jsonl 的 truth_zone vs _current_zone
方法: 字符串直接比较
信任度: 100%
```
### 1.3 渲染完整性 — fulltext_block_mapping_summary.json
```yaml
输入: fulltext_block_mapping_summary.json
found_in_fulltext=false 且 role ∉ {noise, figure_inner_text, frontmatter_noise}
方法: 前80字符子在渲染全文中的存在性检查
信任度: 高(排除 noise 后),注意子串匹配微小误报可能
输出: 真正在 fulltext 中丢失的 body_paragraph / reference_item / backmatter_body 等
```
### 1.4 图/表未匹配资产 — figure_table_ownership_summary.json
```yaml
输入: figures.unmatched_asset_count, tables.unmatched_asset_count
方法: 直接计数
信任度: 100%
输出: 有未匹配资产的 paper未匹配数量
注意: 不判断为什么。vision 看具体原因。
```
### 1.5 覆盖完整性 — coverage_check.json
```yaml
输入: coverage_check.json 的 status, missing_block_ids
信任度: 100%
```
### 1.6 字体一致性 — blocks.structured.jsonl
从每个 block 的 `span_signature``span_metadata` 提取:
```yaml
输入: blocks.structured.jsonl 中所有 text block 的 span_signature
(font_family_norm, font_size_bucket, bold, italic)
方法: 按 role 分组,检查组内一致性
信任度: PDF 直接提取100% 精确
```
**具体检查项:**
```
A. 同一 role 内 font_family_norm 一致吗?
- body_paragraph 应该全是同一字体(如 MyriadPro-Light
- 如果某个 body_paragraph 的 font_family 与其他不同 → 混用字体
B. 同一 role 内 font_size_bucket 一致吗?
- 所有 body_paragraph 的 font_size_bucket 应相同
- 差异 > 1pt → 字号不一致
C. 标题层次递减正确吗?
- 按 page 分组,比较 section_heading / subsection_heading 的 font_size
- H1 > H2 > H3 在字体大小上应有明显递减
D. 同一 block 内混用字体吗?
- span_metadata 有多个 entries 且 font 不同 → 可能是加粗/斜体标记混入
- 检查是否合理(如关键词加粗)还是问题(同一字体错误嵌入)
E. 加粗/斜体使用一致吗?
- 所有 section_heading 的 bold=true
- 所有 body_paragraph 的 bold=false
```
### 1.7 排版布局 — blocks.structured.jsonl + bbox
从每个 block 的 `bbox` 坐标提取:
```yaml
输入: blocks.structured.jsonl 的 bbox [x0, y0, x1, y1]
page_width, page_height
```
**具体检查项:**
```
A. 对齐方式检测:
每页取 body_paragraph 的 x0, x1 坐标:
- 如果所有 x0 相同 → 左对齐 (ragged right)
- 如果所有 x1 相同且 x0 不同 → 右对齐
- 如果 x0 和 x1 都跨block一致 → 居中对齐?
- 如果 x0 都相同但 x1 不同(各行不同长度)+ x1 抵边 → 两端对齐(justified)
- 跨页一致吗?
B. 列检测:
每页对 body_paragraph 的 x-center 做聚类:
- 1个聚类 → 单栏
- 2个聚类 → 双栏(和 expected 一致?)
- 聚类中心 x-center 分布均匀?
C. 页边距一致性:
每页 body_paragraph 的 min(x0) 应大致相同(左页边距)
每页 body_paragraph 的 max(x1) 应大致相同(右页边距)
跨页比较左/右边距是否一致
D. 行间距检测:
同一列相邻 body_paragraph 的 y0 差值减去前一个 block 的高度
= 段间距
跨 block 段间距一致吗?
E. 孤行/孤段检测:
如果一页上某个 body_paragraph 的 height < 正常行高的1.5倍
且它在页面顶部或底部 → orphan 或 widow
```
### 1.8 引用区间完整性 — reference_span_audit.json
```yaml
输入: reference_span_audit.json 的 status, inside_block_ids
方法: status == "HOLD" → 区间未通过验证
inside_block_ids 中 role ≠ reference_item/heading → 可能 intrusion
信任度: 状态可靠intrusion 需要 vision 确认
```
---
## 2. `[VISION]` 必须看图片
以下检查代码**没有所需元数据**,必须看 `page_NNN.png`
### 2.1 图/表视觉验证
```
- 子面板覆盖:一个 figure 的 asset 列表覆盖了所有视觉上的子面板吗?
- 子面板合并2x2 的 grid 被合并为 1 个 figure 还是 4 个独立的?
- caption 位置:在图上方/下方?跨页?
- caption 语义:文字描述的内容与图上数据一致吗?(代码读不了图内容)
- 表布局HTML 表渲染正确?图片表完整无裁剪?
- 角色误标media_asset 实际上是 tablefigure_caption 实际上是 section_heading
```
### 2.2 图像质量
```
- 分辨率:模糊/锯齿/像素化?
- 仪器截屏:显微镜软件、流式细胞仪输出?
- 对比度:前景/背景区分足够?
```
### 2.3 颜色可达性(仅限图片中的颜色)
```
- 图片本身的配色(热图、荧光图等)
- 是否只依赖红/绿区分条件?
- 注意:文本颜色在 span_metadata.color 中,用代码检查
```
### 2.4 统计完整性(图中数据 vs caption 描述)
```
- 图中显示的误差棒/显著性标记与 caption 描述一致?
- N 值标注了吗?
- p 值标注与图例对应?
- 热图 colorbar 标注完整?
```
### 2.5 Chart 类型识别 + 深度分析
```
识别 chart 类型 → 路由到 paperforge/skills/paperforge/atoms/chart-reading/{TYPE}.md
然后用对应指南做深度检查。
```
### 2.6 引用区间边界验证
```
- 参考页第一页body 在 "References" 前结束了吗?
- 过渡页body 和 ref 没有交错?
- reference_zone 外的 reference_item 是否真的是引用条目?
- intrusion candidate 是真的还是 span 边界误标?
```
---
## 3. 不可信自动化结果(不用)
以下数据不作为 finding只做导航
| 数据 | 问题 | 替代用法 |
|------|------|---------|
| `same_page_boundary_error` (audit_report.json) | 纯页面角色计数,正常布局也被标 | vision 优先审这些页 |
| `object_ownership_error` (audit_report.json) | 只报 ambiguous/unresolved漏了大批量 unmatched_assets | 改为读 unmatched_asset_count |
| noise block 的 render_mapping_error | noise 不该在 fulltext 中 | 排除 noise 后看 |
| vision 做字体/颜色检查 | 不准PDF 元数据更精确 | 用 blocks.structured.jsonl |
---
## 4. 输出格式
```jsonl
{
"block_id": "p3:12",
"page": 3,
"review_status": "reviewed",
"truth_role": "figure_asset",
"truth_zone": "display_zone",
"truth_reference_membership": "outside",
"evidence": {"annotated_page": "annotated_pages/page_003.png", "method": "visual+bbox"},
"short_reason": "Fig. 2A MRI image — role and zone correct",
"vision_checks": {
"subpanels_merged": "A (2 of 2 panels matched)",
"image_quality": "OK",
"chart_type": null
}
}
```
`vision_checks` 可选,只记录 vision 实际检查的维度,未检查的用 `null`
---
## 5. 工作流程
```
1. 跑 [CODE]
diff_audit.py → role/zone mismatch 列表
fulltext_block_mapping → 真实渲染丢失(排除 noise
figure_table_ownership → unmatched_asset_count
coverage_check → 缺失 block
blocks.structured.jsonl → 字体一致性、排版异常
2. 决定 vision 目标
优先:
- code 发现的 role mismatch block
- unmatched_asset > 0 的 figure
- body/reference 在 fulltext 丢失的 block
- 参考页第一页
- figure-heavy 页
- coverage FAIL 的 page
3. 逐 block vision [VISION]
对选中 block:
看 annotated page → 确认角色/区域
如果是 figure → 子面板、质量、chart 路由
4. 输出
block_review.jsonl 只写 vision 确认过的 block
不编造未看内容
```

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# OCR Vision Audit Templates
> **Purpose:** Structured prompts for vision agents. Each template pairs with a `--recipe` from `audit_helpers.py`.
> The agent workflow: (1) run `audit_helpers.py --recipe figure_map` to get JSON → (2) read this template → (3) dispatch vision with data + template → (4) vision reports findings.
>
> **After running these 4 templates**, read `ocr-vision-audit-master.md` for the deep quality pass:
> per-role cross-reference pathways, typography checks, chart-type routing to `paperforge/skills/paperforge/atoms/chart-reading/*.md`, figure/table quality checks.
---
## Template 1: Figure Verification
**Data source:** `audit_helpers.py --recipe figure_map --key {KEY}`
**Vision agent prompt (replace {KEY}, {DATA_JSON}, {PAGE_LIST}):**
```
You are auditing figure matching for paper {KEY}. Below is a structured summary
of every figure the pipeline detected — matched, ambiguous, and unresolved.
FIGURE DATA:
{DATA_JSON}
Annotated pages are at:
audit/{KEY}/annotated_pages/page_NNN.png (color-coded block rectangles)
audit/{KEY}/annotated_pages/page_NNN_index.json (maps label numbers to block IDs)
For EACH figure in the data, look at the corresponding annotated page(s) and answer:
### For every figure:
1. VISUAL CONFIRMATION: Find the colored rectangle(s) for this figure on the annotated page.
- The label numbers on the PNG correspond to `block_id` in the data.
- The index JSON maps label_number → block_id, role, bbox.
- TRACE: Find the caption block first (its label number), then find each asset block.
2. ASSET COVERAGE: Does the set of colored boxes cover ALL visible sub-panels of this figure?
- Count how many sub-panels the figure has (from the colored boxes on the page).
- Compare with `assets` list in the data. Are any sub-panels MISSING? Are any EXTRA?
- If data says N assets but visually you see M sub-panels: report the discrepancy.
3. CAPTION CORRECTNESS: Is the caption text (shown in the data) visually the correct caption for this figure?
- Is the caption block positioned correctly relative to the figure (below, above, or side-by-side)?
- Does the caption text match what you see on the page?
- Is it a REAL caption (description of the figure), not a section heading or body text?
4. SUB-PANEL MERGING: Are sub-panels of the SAME figure correctly grouped?
- If the page has a 2x2 grid of images with ONE shared caption, they should be ONE figure.
- If the data shows them as separate figures: that's a merge failure.
- If the data shows them as one figure with N assets: check that N matches visual sub-panels.
5. CROSS-PAGE CHECK: If a figure's caption is on a different page than its assets:
- Is this correct (caption on page N+1, image on page N)? Or is it a mismatch?
- Look at both pages to confirm.
6. ROLE MISLABELS:
- Is any `figure_caption` block actually a section heading? (e.g., "Figure 3. In vitro evaluation..." at the top of a new section)
- Is any `figure_asset` / `media_asset` block actually a table?
- Is any `figure_caption` actually just a sub-panel label ("Fig. 6" only, no description)?
### For each figure, report:
```
Fig {N} — page {P} — status: {OK / PROBLEM}
Issue: {specific problem description}
Evidence: {what you see on the annotated page that supports this}
```
### After checking all figures, provide a summary:
```
Total figures: {N}
OK: {M}
Problems found: {K}
Problem details:
Fig X: [one-line issue]
...
```
### Common patterns to watch for:
- **Truncated label as standalone figure:** "Fig. 6" with no description text, next to a long caption block below → these should be ONE figure with the long text as caption.
- **Multi-panel grid as separate figures:** 4 images in a 2x2 grid, each with "Fig. N" label, one shared caption below → should be ONE composite figure.
- **Caption between two figures:** "Fig. 2" caption sandwiched between Fig 2 image above and Fig 3 image below → caption belongs to the image ABOVE.
- **Empty/phantom blocks in figure area:** A colored box with no visible content inside → the block detection created a ghost.
- **Cross-page orphan:** Caption on page N, image on page N-1 → normal for preproofs.
```
---
## Template 2: Frontmatter Verification
**Data source:** `audit_helpers.py --recipe frontmatter_map --key {KEY}`
**Vision agent prompt:**
```
You are auditing page 1 (frontmatter) for paper {KEY}.
FRONTMATTER DATA:
{DATA_JSON}
Annotated page: audit/{KEY}/annotated_pages/page_001.png
The data lists every block on page 1, top-to-bottom, with its pipeline-assigned role.
Your job: verify each block's role against what you VISUALLY see on the page.
### For each block, answer:
1. ROLE CHECK: Is the assigned role correct?
- paper_title: should be the LARGEST text near the top, centered or left-aligned.
- authors: multiple names, usually below the title, smaller font.
- affiliation: institutional addresses, below authors.
- abstract_heading / abstract_body: "Abstract" label + paragraph text.
- frontmatter_noise: journal name, article type badge, publisher strip — small text at page edges.
- frontmatter_support: correspondence, DOI, dates.
2. BADGE CHECK: Is there a "HIGHLIGHTED PAPER" or "RESEARCH ARTICLE" badge?
- If the data labels it as authors → WRONG.
- If the data labels it as noise → correct.
3. MISSING ROLES: Are any expected roles missing?
- If data says `missing_expected: ["paper_title"]` → check if the title is absorbed into another block.
- If data says `missing_expected: ["abstract_heading"]` → check if the abstract exists but is labeled as body_paragraph.
4. ORDERING: The blocks in the data are sorted top-to-bottom. Is this order visually correct?
- Expected: title → authors → affiliation → (badges/noise mixed in) → abstract → keywords → body text.
- If the order looks wrong visually, report the correct order.
### Report format:
```
Page 1 — {paper_title}
Roles OK: {list of correct roles}
Roles WRONG:
p1:{block_id}: labeled as {role}, should be {correct_role}
Missing: {list}
Badge issue: {yes/no + detail}
```
```
---
## Template 3: Reference Verification
**Data source:** `audit_helpers.py --recipe reference_map --key {KEY}`
**Vision agent prompt:**
```
You are auditing reference completeness for paper {KEY}.
REFERENCE DATA:
{DATA_JSON}
Annotated pages are at audit/{KEY}/annotated_pages/. Focus on:
- The first reference page (where references begin)
- The last reference page (where references end)
- Any "transition_pages" listed in the data
### Check these specific things:
1. REFERENCE BOUNDARY: On the first reference page, is there a clean boundary between body text and references?
- Look for the "References" heading (colored as reference_heading).
- Body text (green) should STOP before this heading.
- If body paragraphs appear AFTER the "References" heading → intrusion.
2. INTRUSIONS: The data lists "real_intrusions" — body_paragraph or backmatter blocks inside the reference zone.
- If empty: no intrusions detected.
- If not empty: look at the specific pages listed. Are these REALLY inside the reference zone?
- Note: noise blocks (gray) between reference items are NORMAL (page numbers, headers).
3. ZONE GAPS: The data lists references not in `reference_zone`.
- Look at the listed pages. Are these reference items that should be in reference_zone?
- If ALL refs on a page are in the wrong zone: the zone assignment failed for that page.
4. TRANSITION PAGES: Pages where body and references co-exist.
- Look at the page: is the visual boundary clean?
- Is there body text that should have ended before the references?
5. REFERENCE NUMBERING: The data lists missing or duplicate reference numbers.
- This is a data-derived check. No visual verification needed.
- Missing numbers may indicate references absorbed into body text → check visually if the missing references appear as body paragraphs.
### Report format:
```
References — {total_references} total
Span: {start} → {end}
Boundary clean: {yes/no}
Real intrusions: {count or "none"}
Zone issues: {count or "none"}
Numbering gaps: {list or "none"}
Visual findings:
[page-specific observations]
```
```
---
## Template 4: Body Text Verification
**Data source:** `audit_helpers.py --recipe body_text_map --key {KEY}`
**Vision agent prompt:**
```
You are auditing body text cleanliness for paper {KEY}.
BODY TEXT DATA:
{DATA_JSON}
The data lists, per page, every body_paragraph, noise, unknown_structural, and
other content block with their bboxes, zones, and text previews.
Annotated pages at audit/{KEY}/annotated_pages/page_NNN.png
### For pages flagged in the data:
1. NOISE IN CONTENT AREA: Blocks with `flag: text_in_content_area` or `flag: empty_in_content_area`.
- Look at the specific page. Is the noise block actually sitting in body text?
- Is it page furniture (page number, header) that happens to have non-edge coordinates?
- Is it a phantom (empty box with no visible content)?
2. BODY TEXT WITH EMPTY TEXT: Body_paragraph blocks with `flag: empty_text_*`.
- Look at the bbox on the annotated page. Is there visible text at this position?
- If yes: OCR missed the text → PDF backfill needed.
- If no: the block is a phantom that should be removed.
3. LARGE GAPS between body paragraphs (gap_px > 100).
- Look at what's in the gap (listed in `blocks_in_gap`).
- Is there supposed to be a figure, heading, or table here?
- Is it a two-column layout where the gap is the right-column text?
4. TWO-COLUMN SUSPICION: If a page has body paragraphs with widely different x-centers.
- Look at the page layout. Is it genuinely two-column?
- Do the left and right columns each have coherent reading order?
### Report format:
```
Body text — {page_count} pages checked
Pages with noise in content: {list}
Pages with empty body text: {list}
Pages with large gaps: {list}
Per-page findings:
Page {N}: [specific observations]
```

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# Scripts
- `ocr_truth_audit.py` stages OCR audit artifacts and writes deterministic helper summaries under `audit/<paper_key>/`.
- It requires an explicit external OCR root via `--source-root` or `PAPERFORGE_OCR_ROOT`.
- It is developer-only and separate from `scripts/dev/` so the repo-local `paperforge-development` skill can evolve without touching the PaperForge product workflow.

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#!/usr/bin/env python3
"""Differential audit: compare existing block_review.jsonl truth against current pipeline output.
Identifies blocks where pipeline role/zone now matches or still differs from human truth.
Marks resolved entries and flags blocks needing re-audit. Updates block_review.jsonl in-place.
Usage:
python diff_audit.py <KEY> --source-root D:/path/to/ocr [--audit-root D:/path/to/audit]
"""
from __future__ import annotations
import argparse
import json
import sys
from collections import defaultdict
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[5]))
from paperforge.worker.ocr_artifacts import artifact_paths_for_root
# Canonical role map: alias → pipeline output role name.
_CANONICAL_ROLE = {
"media_asset": "figure_asset",
"structural_noise": "noise",
"author_list": "authors",
"running_header": "noise",
"page_marker": "noise",
"frontmatter_metadata": "frontmatter_noise",
"separator": "noise",
}
def _canonical(role: str) -> str:
return _CANONICAL_ROLE.get(role, role)
def _load_jsonl(path: Path) -> list[dict]:
if not path.exists():
return []
return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()]
def _write_jsonl(path: Path, rows: list[dict]) -> None:
with path.open("w", encoding="utf-8") as f:
for row in rows:
f.write(json.dumps(row, ensure_ascii=False) + "\n")
def main() -> None:
ap = argparse.ArgumentParser(description="Diff audit: compare truth roles with current pipeline")
ap.add_argument("key")
ap.add_argument("--source-root", dest="source_root", required=True)
ap.add_argument("--audit-root", dest="audit_root", default=None)
args = ap.parse_args()
source_root = Path(args.source_root)
audit_root = Path(args.audit_root) if args.audit_root else Path("audit")
paper_audit = audit_root / args.key
review_path = paper_audit / "block_review.jsonl"
changed_path = paper_audit / "changed_blocks_after_fallback.json"
reviews = _load_jsonl(review_path)
if not reviews:
print(f"No block_review.jsonl at {review_path} — nothing to diff.")
return
artifacts = artifact_paths_for_root(source_root, args.key)
if not artifacts.blocks_structured.exists():
print(f"ERROR: No structured blocks at {artifacts.blocks_structured}")
sys.exit(1)
structured = _load_jsonl(artifacts.blocks_structured)
# Index structured by key
struct_by_key: dict[str, dict] = {}
for block in structured:
page = block.get("page", 0)
bid = block.get("block_id")
if page is None or bid is None:
continue
key = f"p{page}:{bid}"
struct_by_key[key] = block
matches_truth = 0
needs_reaudit = 0
changed_items: list[dict] = []
for review in reviews:
bid = review.get("block_id", "")
truth_role = review.get("truth_role", "")
truth_zone = review.get("truth_zone", "")
current = struct_by_key.get(bid)
if not current:
continue
pipe_role = current.get("role", "")
pipe_zone = current.get("zone", "")
pipe_text_len = len(str(current.get("text", "")).strip())
role_match = _canonical(pipe_role) == _canonical(truth_role)
zone_match = not truth_zone or pipe_zone == truth_zone
if role_match:
review["_pipeline_verified"] = True
review["_current_role"] = pipe_role
matches_truth += 1
else:
review["_needs_reaudit"] = True
review["_current_role"] = pipe_role
review["_current_zone"] = pipe_zone
needs_reaudit += 1
changed_items.append({
"block_id": bid,
"truth_role": truth_role,
"pipe_role": pipe_role,
"pipe_zone": pipe_zone,
"pipe_text_len": pipe_text_len,
"role_match": role_match,
"zone_match": zone_match,
})
# Write summary
summary = {
"paper": args.key,
"total_reviewed": len(reviews),
"pipeline_verified": matches_truth,
"need_reaudit": needs_reaudit,
"changed_blocks": changed_items,
}
changed_path.write_text(json.dumps(summary, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")
# Normalize truth_role to canonical form in place, so future diffs
# match even without the alias map.
for review in reviews:
raw = str(review.get("truth_role") or "")
canonical = _canonical(raw)
if canonical != raw:
review["truth_role"] = canonical
# Write back updated block_review.jsonl
_write_jsonl(review_path, reviews)
print(f"Paper: {args.key}")
print(f" Total reviewed: {len(reviews)}")
print(f" Pipeline verified (role matches truth): {matches_truth}")
print(f" Need re-audit (role still wrong): {needs_reaudit}")
print(f"Written: {changed_path}")
print(f"Updated: {review_path}")
if __name__ == "__main__":
main()

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@ -1,117 +0,0 @@
from __future__ import annotations
import argparse
import json
from pathlib import Path
REQUIRED_FIELDS = [
"block_id",
"page",
"review_status",
"truth_role",
"truth_zone",
"truth_reference_membership",
]
def build_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(description="Verify OCR truth-review coverage against audit_scope.json")
parser.add_argument("audit_dir", help="Path like audit/CAQNW9Q2")
return parser
def _load_json(path: Path) -> dict:
return json.loads(path.read_text(encoding="utf-8"))
def _load_jsonl(path: Path) -> list[dict]:
rows: list[dict] = []
if not path.exists():
return rows
for line in path.read_text(encoding="utf-8").splitlines():
line = line.strip()
if not line:
continue
rows.append(json.loads(line))
return rows
def _write_json(path: Path, payload: dict) -> None:
path.write_text(json.dumps(payload, indent=2, ensure_ascii=False), encoding="utf-8")
def verify(audit_dir: Path) -> tuple[int, dict]:
scope_path = audit_dir / "audit_scope.json"
review_path = audit_dir / "block_review.jsonl"
if not scope_path.exists():
raise SystemExit(f"Missing audit scope: {scope_path}")
if not review_path.exists():
raise SystemExit(f"Missing block review file: {review_path}")
scope = _load_json(scope_path)
reviews = _load_jsonl(review_path)
required = {str(item): True for item in scope.get("required_block_ids", [])}
reviewed_valid: dict[str, dict] = {}
invalid_rows: list[dict] = []
page_counts: dict[int, int] = {}
for row in reviews:
block_id = str(row.get("block_id", "")).strip()
if not block_id:
invalid_rows.append({"block_id": None, "reason": "missing_block_id", "row": row})
continue
missing_fields = [field for field in REQUIRED_FIELDS if row.get(field) in (None, "")]
if row.get("review_status") != "reviewed":
missing_fields.append("review_status=reviewed")
evidence = row.get("evidence") or {}
if not isinstance(evidence, dict) or not evidence.get("annotated_page"):
missing_fields.append("evidence.annotated_page")
if missing_fields:
invalid_rows.append({"block_id": block_id, "reason": "missing_fields", "fields": missing_fields})
continue
reviewed_valid[block_id] = row
page = int(row.get("page", 0) or 0)
if page > 0:
page_counts[page] = page_counts.get(page, 0) + 1
missing_block_ids = sorted([block_id for block_id in required if block_id not in reviewed_valid])
missing_pages = []
for page_row in scope.get("selected_page_requirements", []):
page = int(page_row.get("page", 0) or 0)
if page_row.get("must_review_page") and page_counts.get(page, 0) == 0:
missing_pages.append(page)
status = "PASS"
if invalid_rows or missing_block_ids or missing_pages:
status = "FAIL"
coverage_ratio = (len(required) - len(missing_block_ids)) / len(required) if required else 1.0
report = {
"paper_key": audit_dir.name,
"mode": scope.get("mode"),
"required_block_ids": sorted(required.keys()),
"reviewed_block_ids": sorted(reviewed_valid.keys()),
"missing_block_ids": missing_block_ids,
"missing_pages": missing_pages,
"invalid_rows": invalid_rows,
"coverage_ratio": coverage_ratio,
"status": status,
}
return (0 if status == "PASS" else 1), report
def main(argv: list[str] | None = None) -> int:
parser = build_parser()
args = parser.parse_args(argv)
audit_dir = Path(args.audit_dir)
if not audit_dir.exists():
raise SystemExit(f"Audit dir not found: {audit_dir}")
code, report = verify(audit_dir)
_write_json(audit_dir / "coverage_check.json", report)
print(json.dumps(report, indent=2, ensure_ascii=False))
return code
if __name__ == "__main__":
raise SystemExit(main())

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@ -1,210 +0,0 @@
# OCR Truth Audit
Inputs:
- explicit `paper_key`, or current paper from active context
- `mode: strict | high-risk`
## Pre-flight Checklist
- [ ] Confirm this is developer/internal OCR audit work.
- [ ] Resolve one target paper.
- [ ] Confirm mode: `strict` or `high-risk`.
- [ ] Do not start by writing expectations or fixtures.
- [ ] Use visual and artifact truth first.
- [ ] Know the report contract in `../atoms/ocr-audit-report-schema.md`.
- [ ] Know the page ranking contract in `../atoms/ocr-page-risk-scoring.md`.
- [ ] Know the canonical role list in `../atoms/ocr-canonical-roles.md``truth_role` MUST be from that list.
## Workflow
1. Resolve the paper.
Accept an explicit `paper_key`; otherwise use the current paper in context.
Also resolve the OCR root explicitly. The literature/OCR vault is outside the repo. Pass it with `--source-root` or set `PAPERFORGE_OCR_ROOT`.
2. Refresh or check required artifacts.
Run `../scripts/ocr_truth_audit.py` with `--refresh-artifacts` when you need a fresh rebuild. Confirm availability of `block_trace`, `annotated_pages`, structured block artifacts, rendered `fulltext`, document-structure artifacts, and relevant figure/table artifacts.
3. Verify artifact freshness before auditing.
Check that the paper PDF and derived artifacts belong to the same rebuild generation. At minimum compare fingerprints for `result_json`, raw/structured blocks, document structure, figure/table inventories, reader object outputs, and `fulltext`.
4. Stop on stale artifacts.
If the required artifacts are out of sync, stop with `AUDIT_BLOCKED: stale artifacts` and record which artifacts mismatch.
5. Generate helper summaries.
Materialize helper outputs under `audit/<paper_key>/` via `../scripts/ocr_truth_audit.py`, but treat them as accelerators only, not truth.
6. Inspect truth from evidence.
The audit is split into **five phases**. Phase 6a-6d use the 4 recipes + 4 templates.
Phase **6e** is the deep quality pass using the master atom.
Work through them in this order.
Each domain has a **data map** (run the recipe) and a **vision template** (read the atom).
**6a. Figure verification (most error-prone — do this first).**
```bash
python .opencode/skills/paperforge-development/scripts/audit_helpers.py --recipe figure_map --key {KEY}
```
This prints a JSON listing every figure: caption page/text, asset blocks with bboxes,
match status, candidates, panel labels, cross-page flags.
Then read `../atoms/ocr-vision-audit-templates.md` → "Template 1: Figure Verification".
Dispatch a `vision` subagent with the figure_map JSON + that prompt template.
The vision agent checks: asset coverage, caption correctness, sub-panel merging,
cross-page pairing, role mislabels. Reports discrepancies between pipeline data and
visual truth.
**6b. Frontmatter verification.**
```bash
python .opencode/skills/paperforge-development/scripts/audit_helpers.py --recipe frontmatter_map --key {KEY}
```
Then read `../atoms/ocr-vision-audit-templates.md` → "Template 2: Frontmatter Verification".
Dispatch `vision` subagent with the frontmatter JSON + template.
Checks: role correctness on page 1, badge mislabel, missing roles, ordering.
**6c. Reference verification.**
```bash
python .opencode/skills/paperforge-development/scripts/audit_helpers.py --recipe reference_map --key {KEY}
```
Then read `../atoms/ocr-vision-audit-templates.md` → "Template 3: Reference Verification".
Dispatch `vision` subagent with the reference JSON + template.
Checks: reference boundary, real intrusions, zone gaps, transition pages.
**6d. Body text verification (only flagged pages need vision).**
```bash
python .opencode/skills/paperforge-development/scripts/audit_helpers.py --recipe body_text_map --key {KEY}
```
Then read `../atoms/ocr-vision-audit-templates.md` → "Template 4: Body Text Verification".
Most pages pass on data alone. Dispatch `vision` only for pages with
flagged gaps, noise-in-content, or empty body text blocks.
**6e. Deep quality + typography audit (new — extends all 4 domains).**
After the 4 recipe-driven vision passes, read `../atoms/ocr-vision-audit-master.md`.
This atom provides per-role cross-reference pathways, typography checks,
figure/table quality checks, chart-type routing to the chart-reading atoms,
and full-page layout audit.
For each block that passed the recipe check, dispatch an additional vision pass
if the block is Tier A (figure/table/structured) or if the page has typography flags.
The master atom tells you which data files to cross-reference and what to look for.
**Color reference for annotated pages:** Each role has a distinct color:
- dark blue: `paper_title` `authors` `affiliation` `frontmatter_*`
- purple: `abstract_heading` `abstract_body`
- orange/red: `section_heading` `subsection_heading` `sub_subsection_heading`
- green: `body_paragraph`
- red: `reference_heading` `reference_item`
- purple-brown: `backmatter_*`
- amber/gold: `figure_asset` `media_asset` `figure_caption*` `table_caption*` `figure_inner_text`
- teal: `structured_insert*` `non_body_insert`
- gray: `noise` `footnote` `unknown_structural`
The annotated pages show what the pipeline decided. Your job is to judge whether
that matches visual truth. The companion index (`page_*_index.json`) maps label
numbers to block IDs for cross-reference.
7. Write audit outputs.
Produce the required reports and summaries using `../scripts/ocr_truth_audit.py` plus the schema in `../atoms/ocr-audit-report-schema.md`.
8. Perform visual block review.
After prep outputs are written, inspect the selected pages and write `audit/<paper_key>/block_review.jsonl`. Every reviewed block must be grounded in page visuals plus bbox/artifact evidence.
**`truth_role` MUST be one of the canonical roles in `../atoms/ocr-canonical-roles.md`.**
Do not invent role names. The list includes `paper_title`, `authors`, `abstract_body`, `section_heading`, `body_paragraph`, `reference_item`, `backmatter_body`, `figure_caption`, `table_caption`, `noise`, and all other final pipeline roles.
Using old names (e.g. `media_asset` for `figure_asset`, `author_list` for `authors`, `structural_noise` for `noise`) is a workflow violation — `diff_audit.py` normalizes them, but the audit should be correct from the start.
Each line must include `block_id`, `page`, `review_status`, `truth_role`, `truth_zone`, `truth_reference_membership`, and `evidence` with `annotated_page` and `method`. Example:
```json
{"block_id":"p5:9","page":5,"review_status":"reviewed","truth_role":"body_paragraph","truth_zone":"body_zone","truth_reference_membership":"outside","evidence":{"annotated_page":"annotated_pages/page_005.png","method":"visual+bbox"},"short_reason":"Conclusion body before references, not backmatter."}
```
Use the page index to find a block's current role/zone before judging. Color category helps orient: red blocks are reference candidates, purple are backmatter candidates, etc.
For deep quality checks, see `../atoms/ocr-vision-audit-master.md` section 3 (chart quality),
section 4 (page typography), and section 2 (per-role analysis with quality dimensions).
8.5. Record quality findings in block_review.jsonl.
Extend each block_review.jsonl entry with optional fields `quality_checks` and `page_typography`
as described in `../atoms/ocr-vision-audit-master.md` section 5. Use `null` for unchecked dimensions.
9. Verify review coverage.
Run `../scripts/verify_review_coverage.py` against the paper audit directory. If required blocks are missing for the chosen mode, the audit is incomplete.
## Script Entry Point
Use:
```bash
python .opencode/skills/paperforge-development/scripts/ocr_truth_audit.py CAQNW9Q2 --source-root D:/YOUR/VAULT/System/PaperForge/ocr --mode high-risk --refresh-artifacts
```
For strict mode:
```bash
python .opencode/skills/paperforge-development/scripts/ocr_truth_audit.py DWQQK2YB --source-root D:/YOUR/VAULT/System/PaperForge/ocr --mode strict --refresh-artifacts
```
Coverage verification:
```bash
python .opencode/skills/paperforge-development/scripts/verify_review_coverage.py audit/DWQQK2YB
```
10. Classify findings.
Classify every real error into the frozen taxonomy. Use `audit_truth_gap` only when the audit layer itself misses or distorts block-level truth.
11. Recommend disposition.
For each finding, recommend `repair` when it reflects a pipeline defect worth fixing now, or `residual` when it is real but intentionally deferred or outside the current close-out boundary.
## Strict Mode
Strict mode is full-coverage and block-oriented.
- Every block gets a review state.
- Every reviewed block records truth for role, zone, order, object membership, and reference membership.
- Check role correctness against page context.
- Check zone correctness against actual placement.
- Check reading order and fulltext insertion point.
- Check figure/table ownership where applicable.
- Check reference membership and same-page boundary behavior where applicable.
- Do not infer truth from current rendered output as the first step.
Minimum review questions per block:
- What is the true role?
- What is the true zone?
- What blocks should come before and after it?
- Does it belong to a figure or table object?
- Is it inside or outside the accepted reference span?
## High-Risk Mode
High-risk mode is rapid audit for trust-sensitive layout classes.
- Rank pages with the additive score in `../atoms/ocr-page-risk-scoring.md`.
- Prioritize frontmatter pages.
- Prioritize first-reference and mixed reference pages.
- Prioritize same-page body/reference/tail mixes.
- Prioritize post-reference backmatter pages.
- Prioritize figure-dense and table-dense pages.
- Prioritize figure/table ownership and caption-matching failures.
Recommended focus targets:
- `frontmatter`
- `reference_span`
- `same_page_boundary`
- `backmatter`
- `object_ownership`
- `reading_order`
## Truth Rules
Always follow this order:
1. Determine block-level truth from page visuals and artifacts.
2. Record the truth.
3. Compare pipeline behavior against that truth.
Never reverse the order by rewriting expected truth to fit current OCR output.

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@ -1,24 +0,0 @@
# Retrieval Recovery — Phase 1: Unified Contract
> **For agentic workers:** Use TDD. Write failing test, watch it fail, implement minimal fix, verify green.
**Goal:** Restore retrieval correctness by unifying the Python result envelope and fixing the plugin parser/spawn contracts.
**Architecture:** Approach A — Python CLI is sole retrieval owner. Plugin spawns CLI per query, parses one unified PFResult envelope. sql.js deleted.
**Tech Stack:** Python 3.14 (D:/L/OB/Literature-hub/.venv/Scripts/python.exe), TypeScript/esbuild Obsidian plugin, sqlite-vec 0.1.9, FTS5.
## Global Constraints
- Source Corpus (papers, OCR, blocks, metadata, annotations) MUST NOT be modified.
- Retrieval Artifacts (FTS indexes, vec0 tables, companion meta) are disposable.
- Python executable: `D:/L/OB/Literature-hub/.venv/Scripts/python.exe`
- Vault: `D:/L/OB/Literature-hub`
- Repository worktree: `D:/L/Med/Research/99_System/LiteraturePipeline/github-release/.worktrees/retrieval-recovery`
- Test vault for disposable tests: `tests/fixtures/vault`
- All CLI calls use `--vault` flag pointing to the test vault, never the live vault in tests.
- Contract tests must parse real CLI JSON output, not mock it.
- Existing 89 tests must keep passing.
- Commit after every task with Conventional Commits style (repo convention: `feat:`, `fix:`, `chore:`).
---

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@ -1,101 +1,157 @@
---
phase: 02-code-review-command
reviewed: 2026-06-04T15:30:00Z
depth: standard
files_reviewed: 2
phase: 02-code-review
reviewed: 2026-05-14T12:00:00Z
depth: deep
files_reviewed: 1
files_reviewed_list:
- tests/test_ocr_artifacts.py
- tests/test_ocr.py
- paperforge/memory/schema.py
findings:
critical: 0
warning: 1
info: 0
total: 1
warning: 3
info: 2
total: 5
status: issues_found
---
# Phase 2: Code Review Report -- Task 1 OCR Structured Pipeline
# Phase 02: Code Review Report
**Reviewed:** 2026-06-04T15:30:00Z
**Depth:** standard
**Files Reviewed:** 2
**Reviewed:** 2026-05-14T12:00:00Z
**Depth:** deep
**Files Reviewed:** 1
**Status:** issues_found
## Summary
This task creates three TDD contract tests across two files that lock the Phase 1 OCR artifact contract (directory layout, version payload schema, postprocess artifact emission) in a failing state, exactly as specified in the plan. The tests will be made to pass by subsequent tasks.
Reviewed Task 1 implementation: addition of `CREATE_READING_LOG` and `CREATE_PROJECT_LOG` SQL table definitions to `paperforge/memory/schema.py`. The implementation faithfully follows the plan specification with correct SQL syntax, proper registration in `ensure_schema()`, correct `ALL_TABLES` inclusion, and `CURRENT_SCHEMA_VERSION` bumped from 1 to 2. All 5 existing schema unit tests pass. No critical defects were introduced.
The implementation is correct in intent and faithfully follows the plan. However, one code quality defect was found: a missing `Path` import in `tests/test_ocr.py` that creates a fragility when the annotation is evaluated on Python < 3.14 and violates the project's established convention (every other test file imports `Path`).
All 3 new tests fail as expected in the current environment:
- 2 fail with `ModuleNotFoundError` (target module does not exist yet) -- correct
- 1 fails with `AssertionError` (artifact files not written yet) -- correct
All 4 pre-existing tests in `tests/test_ocr.py` continue to pass -- no regression detected.
### Test Failure Diagnostics
| Test | Failure Type | Expected? |
|------|-------------|-----------|
| `test_phase1_artifact_layout_is_paper_local` | `ModuleNotFoundError: No module named 'paperforge.worker.ocr_artifacts'` | YES -- TDD contract, module not yet created |
| `test_raw_and_derived_version_payloads_have_separate_namespaces` | `ModuleNotFoundError: No module named 'paperforge.worker.ocr_artifacts'` | YES -- TDD contract, module not yet created |
| `test_postprocess_writes_phase1_artifacts` | `AssertionError: assert False` at line 169 | YES -- `postprocess_ocr_result()` does not yet write Phase 1 artifacts |
However, three warnings were identified: (1) the foreign key from `reading_log` to `papers` will create a deletion-ordering conflict in `builder.py` once the table is populated (future Task 6 concern), (2) the column name `date` in `project_log` shadows a SQLite built-in function name, and (3) the foreign key column `reading_log.paper_id` lacks an index, which will cause full table scans on lookup queries.
## Warnings
### WR-01: Missing `Path` import in `test_ocr.py` creates annotation fragility
### WR-01: Foreign Key Will Block `DELETE FROM papers` During Rebuild
**File:** `tests/test_ocr.py:154`
**Issue:** The function signature `def test_postprocess_writes_phase1_artifacts(tmp_path: Path) -> None:` references `Path` in a type annotation, but `Path` is not imported in `tests/test_ocr.py`. This file has zero module-level imports -- the only test file in the project with this characteristic. Every other test file consistently uses `from pathlib import Path`.
**File:** `paperforge/memory/schema.py:153` (FK definition), `paperforge/memory/builder.py:84` (DELETE caller)
This works in Python 3.14 due to PEP 649 (deferred annotation evaluation), but it:
- **Fails with `NameError` on Python < 3.14** if the module is imported without `from __future__ import annotations`
- Creates a hidden dependency on the conftest's import order and PEP 649 being active
- Violates the project's established convention (all other test files with `Path` annotations import it explicitly)
**Issue:** The `reading_log` table defines `FOREIGN KEY (paper_id) REFERENCES papers(zotero_key)` without `ON DELETE CASCADE`. During non-schema-change rebuilds in `builder.py`, the code executes `DELETE FROM papers` (line 84) WITHOUT first clearing `reading_log`. Once Task 6 populates `reading_log` from JSONL, this DELETE will fail with an `IntegrityError` because SQLite enforces foreign key constraints on DML operations when `PRAGMA foreign_keys=ON` (which `db.py:34` explicitly enables).
**Fix:** Add `from pathlib import Path` to `tests/test_ocr.py` at module level. This is consistent with the pattern used in `tests/test_ocr_redo.py`, `tests/test_ocr_artifacts.py`, `tests/test_context.py`, and every other test file in the project.
Currently latent because `reading_log` is never populated (Task 6 has not been implemented). Will surface during the Task 6 rebuild flow.
**Fix:**
In `builder.py`, clear `reading_log` (and `project_log`) before deleting `papers`:
```python
# Add to tests/test_ocr.py, before the first test function:
from pathlib import Path
# In builder.py, before the DELETE FROM papers (line 84), add:
conn.execute("DELETE FROM reading_log;")
conn.execute("DELETE FROM project_log;")
```
Alternatively, if the project intentionally uses annotation-only mode for all test files, add `from __future__ import annotations` at the top of `tests/test_ocr.py` (matching `tests/test_ocr_artifacts.py` and `tests/conftest.py`).
Alternatively, add `ON DELETE CASCADE` to the foreign key definition in `schema.py`:
```python
FOREIGN KEY (paper_id) REFERENCES papers(zotero_key) ON DELETE CASCADE
```
## Assessment
### Strengths
1. **Plan alignment:** The implementation matches the plan exactly -- both `test_ocr_artifacts.py` tests and the `test_ocr.py` addition are verbatim from the spec.
2. **Design alignment:** The contract tests correctly reflect the design spec (`docs/superpowers/specs/2026-06-04-ocr-structured-pipeline-design.md`):
- `raw/raw_meta.json` and `raw/source_metadata.json` match Layer 0/1 artifacts
- `canonical/blocks.raw.jsonl` matches Layer 2
- `structure/blocks.structured.jsonl` matches Layer 3
- `raw_version`/`derived_version` payloads match Section 6 version model
3. **Well-scoped scope:** The task did not leak into implementation work -- no production source files were modified, no `ocr_artifacts.py` was prematurely stubbed.
4. **Explicit path assertions:** Using `.as_posix().endswith(...)` in `test_ocr_artifacts.py` correctly handles Windows vs POSIX path separators, making the tests cross-platform.
5. **Clean new file:** `tests/test_ocr_artifacts.py` is small (29 lines), has a single responsibility (contract tests), and is independently importable.
### Defects
| ID | Severity | Description | File:Line |
|----|----------|-------------|-----------|
| WR-01 | Warning | Missing `Path` import in `test_ocr.py` | `tests/test_ocr.py:154` |
### Verification
- Module-level imports absent from `tests/test_ocr.py`: confirmed by `rg` (zero results)
- All other 21 test files import `Path` from `pathlib`: confirmed by `Select-String` across `tests/*.py`
- All 3 new tests fail as expected: confirmed by running `pytest` against both files
- All 4 pre-existing tests still pass: confirmed by `pytest` output
- Design spec alignment: confirmed by reading the design doc
The first approach (explicit DELETE) is preferred because it makes the rebuild flow explicit and doesn't silently cascade deletions that could surprise maintainers.
---
_Reviewed: 2026-06-04T15:30:00Z_
_Reviewer: VT-OS/OPENCODE (gsd-code-reviewer)_
_Depth: standard_
### WR-02: Column Name `date` Shadows SQLite Built-in Function
**File:** `paperforge/memory/schema.py:161`
**Issue:** The `project_log` table uses `date` as a column name (line 161: `date TEXT NOT NULL`). While syntactically valid in SQLite (which allows function names as unquoted identifiers), `date` is a built-in SQL function. This creates ambiguity when reading queries — `SELECT date FROM project_log` works but `SELECT date(created_at) FROM project_log` is ambiguous. More importantly, if this schema is ever ported to another SQL dialect (PostgreSQL, MySQL), `date` is a reserved word and will require quoting.
**Fix:**
Rename the column to `log_date`, `entry_date`, or `recorded_date`:
```sql
-- In CREATE_PROJECT_LOG:
log_date TEXT NOT NULL,
```
Note: This would also require updating the plan's Task 2 (`permanent.py`) and Task 6 (`builder.py`) where the column is referenced. If changing the schema column name is too invasive for this phase, consider adding a comment noting the potential ambiguity.
---
### WR-03: Missing Index on Foreign Key Column `reading_log.paper_id`
**File:** `paperforge/memory/schema.py:142`
**Issue:** The `reading_log` table has a foreign key on `paper_id` (line 142), but no index is created for this column. All queries filtering by `paper_id` (e.g., `get_reading_notes_for_paper()` in `permanent.py`, paper-context lookup) will require full table scans. As the reading log grows, this will degrade query performance.
**Fix:**
Add an index alongside the existing `EVENT_INDEX_SQL` block (following the established pattern in the file):
```python
# After EVENT_INDEX_SQL (line 137), add:
READING_LOG_INDEX_SQL = [
"CREATE INDEX IF NOT EXISTS idx_reading_log_paper ON reading_log(paper_id);",
"CREATE INDEX IF NOT EXISTS idx_reading_log_project ON reading_log(project);",
"CREATE INDEX IF NOT EXISTS idx_reading_log_created ON reading_log(created_at);",
]
```
And register in `ensure_schema()` after the `EVENT_INDEX_SQL` loop:
```python
for idx_sql in READING_LOG_INDEX_SQL:
conn.execute(idx_sql)
```
Also add a project-level index for `project_log`:
```python
PROJECT_LOG_INDEX_SQL = [
"CREATE INDEX IF NOT EXISTS idx_project_log_project ON project_log(project);",
"CREATE INDEX IF NOT EXISTS idx_project_log_created ON project_log(created_at);",
]
```
---
## Info
### IN-01: Test Hardcodes Stale Schema Version
**File:** `tests/unit/memory/test_schema.py:73`
**Issue:** The test `test_get_schema_version_returns_stored_value` inserts `schema_version = '1'` and asserts the returned value equals 1. Since `CURRENT_SCHEMA_VERSION` was bumped to 2, the hardcoded '1' no longer matches the current version. While the test is verifying read-back behavior (not version equality), the stale value could confuse future maintainers who assume the test reflects the current schema version.
**Fix:**
Either update to a version-independent test or clarify with a comment:
```python
# Test uses arbitrary version '1' for read-back verification (not tied to CURRENT_SCHEMA_VERSION)
conn.execute(
"INSERT INTO meta (key, value) VALUES ('schema_version', '1')"
)
conn.commit()
assert get_schema_version(conn) == 1
```
---
### IN-02: `ALL_TABLES` Ordering — Child Tables After Parent (Latent DDL Risk)
**File:** `paperforge/memory/schema.py:175`
**Issue:** The `ALL_TABLES` list orders `papers` (index 1) before its child tables `paper_assets`, `paper_aliases`, `paper_events`, and now `reading_log` (indices 2-7). In `drop_all_tables()`, SQLite with `PRAGMA foreign_keys=ON` will reject `DROP TABLE papers` if any child table contains rows referencing papers. This is currently benign because `drop_all_tables()` is only called when schema versions mismatch — at which point the new `reading_log` table hasn't been populated yet. However, if `drop_all_tables` is ever called on a populated database, the ordering would cause a failure.
**Fix (if desired — pre-existing, not introduced by this change):**
Reorder `ALL_TABLES` so child tables (FK-referencing) appear before parent tables (FK-referenced):
```python
ALL_TABLES = ["paper_fts", "reading_log", "project_log", "paper_events", "paper_aliases", "paper_assets", "papers", "meta"]
```
Note: `paper_fts` is a virtual table and cannot have FK constraints, so its position is flexible.
---
_Reviewed: 2026-05-14T12:00:00Z_
_Reviewer: the agent (gsd-code-reviewer)_
_Depth: deep_

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@ -1,341 +0,0 @@
# PR1: Deterministic Local Fixes — Implementation Plan Draft
**Issues:** 3 (backfill bbox clamp) + 1A (validation-first fallthrough) + 1B (table continuation materialization) + 4 (short-form health profile)
**Implementation order (strict):** 3 → 1A → 1B → 4
**Rationale:** Order minimizes conflict surface. Issue 3 is a pure isolated bug in `ocr_pdf_spans.py`. Issues 1A/1B are both in `ocr_tables.py` and share the same test file, but 1A is the simpler gate change (one `continue` guard), and 1B is the richer continuation helper. Doing 1A first so its passing tests are baseline before 1B's materialization logic. Issue 4 is an independent health-layer change last.
---
## File Map
| File | Role in PR1 |
|------|-------------|
| `paperforge/worker/ocr_pdf_spans.py` | Add `_word_belongs_to_block()` + `_word_center_inside_rect()`; insert word-level filter in `backfill_missing_text_from_pdf()` |
| `paperforge/worker/ocr_tables.py` | Change validation-first `continue` guard (1A); add `_find_table_caption_continuation()` + `_materialize_table_caption()` (1B) |
| `paperforge/worker/ocr_health.py` | Add `_health_profile()`; gate structural_blockers on `short_form`; add report fields `health_profile`, `waived_gates`, `degraded_reason` |
| `tests/test_ocr_pdf_text_fallback.py` | **New file.** Unit tests for backfill word-level filtering |
| `tests/test_ocr_tables.py` | Tests for 1A (validation-first fallthrough) + 1B (split-caption materialization, anti-overreach) |
| `tests/test_ocr_render.py` | Test for render skipping consumed continuation block (1B spillover) |
| `tests/test_ocr_health.py` | Tests for short-form profile behavior |
**No other files modified.** No changes to `ocr_roles.py`, `ocr_figures.py`, pipeline wiring, or any module outside the three listed above.
---
## Issue 3: Backfill Bbox Expansion Overflow
### Validated Root Cause
`backfill_missing_text_from_pdf` at `ocr_pdf_spans.py:687-695` applies a 1%/5% padding margin around the target block's bbox before calling `pdf_page.get_text("words", clip=expanded)`. When a neighbor block is close enough, the expanded clip rectangle overlaps it, and `get_text` returns that neighbor's words as part of the backfill text. The render-layer dedup (5-gram Jaccard ≥0.8) suppresses most duplicates, but:
- 60-80% overlap can leak through the threshold
- A genuinely empty block that needs backfill can be false-rejected if OCR text from the same page is similar enough to the backfill text
### Preferred Low-Risk Approach
**Word-level rejection after expanded extraction.** Keep the expansion for search (it's needed because OCR bboxes can drift from PDF text layer). But filter the returned word list against the original (unexpanded) bbox before reassembling text.
Do NOT change the expansion margin. Do NOT change the overlap dedup threshold. Do NOT change any caller behavior.
**Changes to `ocr_pdf_spans.py`:**
1. Add helper near `_bbox_overlap_ratio` (~line 277):
- `_word_center_inside_rect(word_bbox, block_rect) -> bool` — word center inside rect
- `_word_belongs_to_block(word_bbox, block_rect) -> bool` — center-inside OR ≥30% bbox overlap (tolerates partial misalignment)
2. In `backfill_missing_text_from_pdf` (~line 698), change:
```python
words = pdf_page.get_text("words", clip=expanded)
text = _words_to_text(words)
```
to:
```python
words = pdf_page.get_text("words", clip=expanded)
words = [
w for w in words
if len(w) >= 4 and _word_belongs_to_block(tuple(w[:4]), rect)
]
text = _words_to_text(words)
```
### Rejected Approaches
- **Remove expansion entirely** — breaks alignment tolerance for blocks where OCR bbox is slightly misaligned with PDF text layer. 4DU8LEH2 and similar papers would regress.
- **Change the dedup threshold** — fixes the symptom, not the root cause. Could cause genuine duplicate text in render.
- **Per-page pre-clustering of blocks** — architectural churn for a two-helper fix.
### Tests
New file `tests/test_ocr_pdf_text_fallback.py`:
- `test_backfill_expanded_clip_filters_words_to_original_bbox` — Fake PDF page returns words inside and outside the original bbox. After backfill, only the inside word should be recovered.
- `test_backfill_keeps_slightly_misaligned_words_by_center_or_overlap` — Word just outside rect edge but with center inside (or overlap ≥30%) is still accepted.
### Commit Boundary
```bash
# after tests fail → after implementation passes → commit:
git add paperforge/worker/ocr_pdf_spans.py tests/test_ocr_pdf_text_fallback.py
git commit -m "fix: clamp pdf backfill words to original bbox"
```
---
## Issue 1A: Validation-First Bare "Table N" Fallthrough
### Validated Root Cause
`build_table_inventory` at `ocr_tables.py:193-214` has a guard:
```python
if is_validation_first_candidate and is_weak_truncated:
if not same_page_assets:
held_tables.append(...)
continue # <-- exits unconditionally
```
When same-page assets DO exist (69TA9S8W: 12 bare "Table N" captions on pages with clear table images), the `continue` skips the rest of the matching loop. The weak-explicit path below (lines 215-297) has the spatial gates (`_has_strong_spatial_evidence_for_bare_table`, tie-break) that *could* produce a match, but it never runs.
Key insight: the `continue` was there because without any text evidence, matching seemed pointless. But the weak-explicit path has since been hardened with spatial gating (strong evidence or continuation geometry elevation). The same-page asset may provide enough spatial evidence.
### Preferred Low-Risk Approach
**Add one conditional: only `continue` when there are no same-page assets.** When assets exist, fall through into the existing weak-explicit path. No new scoring, no new gating — just removing the unconditional bypass.
The existing `test_validation_first_table_candidate_with_asset_can_still_match` (test_ocr_tables.py:470-504) already tests the case where the caption has **full text** ("Table 3. Cell counts..."). No test exists for **weak-truncated** + validation-first + same-page asset — that's the exact gap.
**Changes to `ocr_tables.py:193-214`:**
```python
if is_validation_first_candidate and is_weak_truncated:
same_page_assets = [
a for i, a in enumerate(assets)
if i not in used_asset_indices and a.get("page", 0) == caption_page
]
if not same_page_assets:
held_tables.append({
"table_id": f"held_table_{len(held_tables) + 1:03d}",
"caption_block_id": caption.get("block_id", ""),
"page": caption_page,
"caption_text": caption_text,
"table_number": table_num,
"formal_table_number": formal_table_number,
"hold_reason": "insufficient_caption_evidence",
"zone": caption.get("zone", ""),
"style_family": caption.get("style_family", ""),
"marker_signature": caption.get("marker_signature", {}),
})
continue
# same-page asset exists → fall through into weak-explicit matching
```
### Rejected Approaches
- **Add a second scoring path for validation-first** — duplicates the scoring logic. The existing weak-explicit path already handles bare "Table N" via `_bare_table_tie_break`, scoring, and spatial evidence.
- **Change validation-first detection** — the candidate detection is correct; the bug is what happens *after* detection.
- **Match in a separate loop** — the match logic depends on `used_asset_indices` tracking across captions; a separate loop would need to replicate that state machine.
### Tests
In `tests/test_ocr_tables.py`:
- `test_validation_first_bare_table_with_same_page_asset_falls_through` — Block with role=body_paragraph, marker_signature.table_number, display_zone, table_caption_like (validation-first), text="Table 1" (weak_truncated), same-page table asset exists. Expects: held_tables empty, 1 table matched with asset.
**Existing relevant tests that must continue passing:**
- `test_validation_first_table_candidate_remains_stable_under_anchor_first_roles` (line 112) — validation-first WITH full text, already matches
- `test_table_matching_can_hold_when_caption_and_asset_conflict` (line 398) — validation-first + weak_truncated + NO same-page asset, should still hold
- `test_validation_first_table_candidate_with_asset_can_still_match` (line 470) — validation-first + full text + asset, already matches
### Commit Boundary
```bash
# after 1A tests pass, before 1B changes:
git add paperforge/worker/ocr_tables.py tests/test_ocr_tables.py
git commit -m "fix: allow validation-first bare tables to fall through"
```
---
## Issue 1B: Table Continuation Materialization
### Validated Root Cause
This is the split-caption case (2HJSWV3V). OCR breaks a table caption into two adjacent text blocks:
| Block | Text | Role Assigned |
|-------|------|---------------|
| Block 11 | "Table 2" | `table_caption` |
| Block 12 | "Structural parameters of..." | `figure_caption` (WRONG) |
| Block 13 | [table image] | `media_asset` |
Block 12 does not start with "Table", has no table marker, so the table caption collector (line 148: `role in {"table_caption", "table_caption_candidate"}`) never sees it. OCR role assignment (`ocr_roles.py:758-770`) promotes it to `figure_caption` via `body_paragraph + legend_like + figure_title` heuristic.
**Two separate effects:**
1. **Stable caption-completeness bug** — Table 2's full caption is "Table 2 Structural parameters of nanocomposites..." but the table inventory records only "Table 2". Complete text is lost from the table caption.
2. **Conditional matching bug** — If geometry is also weak or the block falls into the validation-first gap (already fixed by 1A), the table can become unmatched. But even after 1A, the matching algorithm scores "Table 2" without the continuation text against the asset — the match might be weaker than it should be.
### Preferred Low-Risk Approach
**Add local continuation detection and materialization inside `build_table_inventory`.** Do NOT merge OCR blocks globally. Do NOT change role assignment. Instead, detect the continuation block after caption collection and merge text/metadata for matching purposes only.
**Implementation details:**
1. Add `_find_table_caption_continuation(caption_block, structured_blocks) -> dict | None`:
- Trigger: current caption is weak-truncated ("Table N")
- Same page
- y-gap between blocks ≤ 25px
- x-overlap ratio ≥ 0.5 OR left-edge delta < 40px
- Continuation role ∈ {figure_caption, body_paragraph, unknown_structural, table_caption_candidate}
- Continuation text does NOT start with Fig/Figure/Scheme/Plate
- No media_asset/table_image sits between the two blocks
2. Add `_materialize_table_caption(caption, continuation) -> (merged_caption, consumed_ids)`:
- Creates a merged caption dict for matching only
- Merges text, extends bbox to cover both blocks
- Tracks continuation's `block_id` in `consumed_block_ids`
3. In the `build_table_inventory` caption loop (~line 183), insert after weak-truncated detection:
```python
materialized_caption = caption
continuation = None
continuation_ids: list[str] = []
if is_weak_truncated:
continuation = _find_table_caption_continuation(caption, structured_blocks)
materialized_caption, continuation_ids = _materialize_table_caption(caption, continuation)
caption_text = materialized_caption.get("text", "")
```
Then pass `materialized_caption` to scoring instead of raw `caption`.
4. Extend `consumed_block_ids` with `continuation_ids` in the final table dict assembly (around lines 448-482).
### Rejected Approaches
- **Merge raw OCR blocks before role assignment** — broader blast radius; affects all downstream consumers (figure pipeline, render, health). Risk of regressions across 33 affected papers.
- **Change role assignment for continuation blocks** — would require `ocr_roles.py` changes and retraining the role-assignment heuristics. Not worth the risk when local detection is precise.
- **Use font/style matching** — unreliable across different OCR outputs; spatial proximity is more robust.
- **Do NOT merge, just improve matching** — leaves caption incomplete in the inventory. Downstream consumers (render, health, export) see truncated text.
### Tests
In `tests/test_ocr_tables.py`:
- `test_split_table_caption_materializes_continuation_stolen_as_figure_caption` — Block1 = "Table 2" (table_caption), Block2 = "Structural parameters..." (figure_caption), same page, small y-gap. Expects: merged caption text starts with "Table 2 Structural", continuation block_id in consumed_block_ids.
- `test_split_table_caption_does_not_steal_real_figure_caption` — Same setup but Block2 starts with "Figure 3." → must NOT be consumed.
- `test_split_table_caption_with_wide_gap_not_materialized` — y-gap = 50px → continuation NOT matched.
In `tests/test_ocr_render.py`:
- `test_materialized_table_caption_continuation_is_skipped_by_render_when_consumed` — Verify that a continuation block in `consumed_block_ids` is excluded from rendered markdown.
### Commit Boundary
```bash
# after 1B tests pass + render test passes:
git add paperforge/worker/ocr_tables.py tests/test_ocr_tables.py tests/test_ocr_render.py
git commit -m "fix: materialize split table caption continuations"
```
---
## Issue 4: Short-Paper Health False Red
### Validated Root Cause
`build_ocr_health` at `ocr_health.py:179-185` unconditionally counts missing abstract, references, and section headings as structural blockers, regardless of paper format. Letters/Editorials/Short Communications ≤2 pages by design lack headings, abstract sections, or reference zones. The health report goes red (structural_blockers ≥ 2 → `overall = "red"`, `needs_rebuild = True`) even when OCR is perfect.
### Preferred Low-Risk Approach
**Add a `page_count`-based health profile selector.** Papers with ≤2 pages enter a `short_form` profile that waives abstract, heading, and references structural-blocker gates. The information is still reported (for transparency), but does not drive the overall color or rebuild decision.
**New fields:**
- `health_profile: "standard" | "short_form"`
- `waived_gates: list[str]` — which gates were waived for this profile
- `degraded_reason: str``"short_paper_format"` when profile is short_form
**Changes to `ocr_health.py`:**
1. Add `_health_profile(page_count: int) -> str`.
2. In `build_ocr_health`, compute profile, then conditionally exempt:
```python
profile = _health_profile(page_count)
waived_gates: list[str] = []
structural_blockers = 0
if profile == "short_form":
waived_gates = ["abstract_found", "section_heading_count"]
if not references_found:
waived_gates.append("references_found")
else:
if not abstract_found: structural_blockers += 1
if not references_found: structural_blockers += 1
if section_heading_count < 2: structural_blockers += 1
```
3. Add report fields: `health_profile`, `waived_gates`, `degraded_reason` (when short_form).
**Edge case:** `references_found` is waived too — short papers often have no numbered references, only footnoted URLs or no reference section at all. The data remains in the report for inspection.
### Threshold Selection
`page_count <= 2` is the safe threshold. Letters (1-2pp), Editorials (1-2pp), Short Communications (2pp). Three-page papers with structure issues should still flag — 3pp is enough for a minimal IMRaD structure.
### Rejected Approaches
- **Auto-detect paper type by role patterns** — over-engineered. Page count is the simplest reliable proxy. A 2-page paper *cannot* have a full IMRaD structure by definition.
- **Reduce threshold instead of waiving** — lowering `section_heading_count` threshold would let short papers through but also weaken the signal for regular papers.
- **Make structural_blockers configurable** — adds complexity without narrowing the blast radius. Direct waiver is simpler.
### Tests
In `tests/test_ocr_health.py`:
- `test_short_form_health_does_not_go_red_for_missing_abstract_headings_and_refs` — page_count=2, no headings, no abstract, no refs → `health_profile == "short_form"`, `overall` not "red", `needs_rebuild == False`, `"abstract_found" in waived_gates`.
- `test_standard_profile_still_flags_missing_structure` — page_count=5, same empty structure → `health_profile == "standard"`, `overall == "red"`.
**Existing tests that must continue passing:**
- All tests passing `page_count=1` with headings present (e.g., `test_health_counts_all_heading_tiers_and_requires_stronger_reference_evidence`, line 4) — must still work fine since they include headings.
- `test_health_report_is_independent_from_ocr_status` (line 23) — page_count=3, should get standard profile.
- `test_ocr_health_includes_span_spine_and_layout_signals` (line 148) — page_count=2 but has signals; must not be affected.
### Commit Boundary
```bash
# after tests pass:
git add paperforge/worker/ocr_health.py tests/test_ocr_health.py
git commit -m "fix: add short-form OCR health profile"
```
---
## Integration Safety
### Regression Verification (must run before PR1 merge)
```bash
python -m pytest \
tests/test_ocr_pdf_text_fallback.py \
tests/test_ocr_tables.py \
tests/test_ocr_render.py \
tests/test_ocr_health.py \
-q --tb=short
```
**Expected: All pass, 0 failures.**
Then run the full OCR regression suite to catch cross-module effects:
```bash
python -m pytest tests/test_ocr_*.py -q --tb=short -x
```
### Cross-Module Risks
| Change | Could affect | Risk level | Mitigation |
|--------|-------------|------------|------------|
| Issue 3 word filter | All blocks going through `backfill_missing_text_from_pdf` | Medium — could reject words that belong to block but are outside bbox | Center-inside OR overlap ≥30% tolerance; existing tests pass |
| Issue 1A fallthrough | Table matching for validation-first bare tables | Low — only adds a matching attempt for cases that were previously ignored | Identical path as weak-explicit; existing bare-table tests guard regressions |
| Issue 1B continuation | Table inventory, render consumed_block_ids | Low — continuation detection gates are tight; render skip for consumed blocks is already an existing pattern | Anti-overreach test guards real figure captions |
| Issue 4 short form | `needs_rebuild` signal for short papers | Low — only changes behavior for page_count ≤ 2, which already lacks structure | Standard profile logic unchanged; all existing tests pass |
### Non-Goals for PR1
- Do NOT change `ocr_roles.py` — role assignment is intentionally untouched
- Do NOT change figure containment or `_container_bbox` — that's PR2
- Do NOT change page-assets clustering — that's PR3
- Do NOT change ownership arbitration — that's PR3
- Do NOT add new dependencies or configuration files
- Do NOT refactor existing helpers into shared modules

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@ -1,195 +0,0 @@
# Approach A — Python CLI as Sole Retrieval Owner
**Date:** 2026-07-10
**Author:** Main (synthesized from latency probes in failure matrix + architecture drift audit)
**Scope:** Evaluate Approach A for the PaperForge Retrieval Experience: **Python CLI is the only query/build execution owner. Plugin invokes a fresh CLI process for M, @, status, build, and control; sql.js is deleted; SQLite/FTS/sqlite-vec and build_state stay Python-owned.**
**Non-goals:** daemon process; sql.js; native Node SQLite module; Chroma migration.
---
## Verdict
**Viability: Strongly viable — the simplest correct path.**
**Recommendation: Implement as the first recovery phase regardless of which long-term architecture is chosen.** Approach A is the only option that can restore retrieval correctness within a single session without introducing new IPC surface or lifecycle complexity. It can later be upgraded to Approach B (add sql.js as read-only cache) or Approach C (add worker) once correctness is proven.
**Fatal risk:** The only fatal risk is the same as today — contract drift between Python payloads and TypeScript parsers. This is mitigated by a unified PFResult envelope enforced by contract tests.
---
## Exact ownership boundary
### Python owns everything retrieval (canonical)
- **Storage:** `paperforge.db` (FTS, vec0, meta, build_state)
- **Schema:** `paperforge/memory/schema.py`
- **M query execution:** `paperforge search --json`
- **@ query execution:** `paperforge retrieve --deep --json`
- **Build execution:** `paperforge embed build|status|stop`
- **Status/health:** `paperforge embed status --json`
- **Result envelope:** one unified `PFResult` across all search/retrieve paths
- **Error taxonomy:** `ok: false` with `error.code` and `error.message`
### Plugin owns UI only
- spawn Python CLI per query
- parse one result envelope (`PFResult`)
- render cards, progress, errors
- manage debounce and abortion (kill child process)
### Explicitly deleted
- `paperforge/plugin/src/services/db.ts` (sql.js service)
- `paperforge/plugin/sql-wasm.wasm`
- `sql.js` from `package.json`
- All sql.js initialization/fallback branches in dashboard
- `vector-runtime-state.json` as authoritative UI truth (may remain as debug snapshot)
- Legacy Chroma production gates in resume/force/delete/status
---
## Observed latency
All measurements from the live Literature-hub vault (D:/L/OB/Literature-hub, 868 papers, 88.9 MB paperforge.db):
| Operation | Time | Notes |
|-----------|------|-------|
| Bare Python child spawn (`python -c pass`) | 73 ms | Floor cost per CLI call |
| `paperforge.cli` import from fresh process | 116 ms | Import chain: config 18ms, db 28ms, search 6ms |
| Full M metadata search spawn (`search knee --json`) | **131 ms** | Cold end-to-end |
| Direct SQLite FTS5 JOIN query (5 results) | 16.4 ms | Query-only, no spawn |
| sqlite-vec extension load | 102.1 ms | One-time per process |
### User-visible latency under Approach A
| Interaction | Expected latency | Perceived |
|-------------|-----------------|-----------|
| Debounced M search (200ms timer) | ~130 ms from spawn | **~330 ms total** (200ms debounce + 130ms spawn) |
| Enter-triggered M search | ~130 ms | Acceptable for explicit action |
| @ deep search (cold) | ~200-300 ms (spawn + vec load + API) | Acceptable |
| @ deep search (warm, sequential) | ~130 ms + API | Acceptable |
| Status/health check | ~130 ms | On settings load — fine |
| Build start | ~130 ms | One-time cost |
### Is ~330ms debounce acceptable?
Yes. The current debounce is 200ms. Adding 130ms spawn gives ~330ms from last keystroke to results. This is within the 200-500ms range where users perceive "instant." The sql.js path was intended to skip the 130ms spawn, but it never worked (Row 1 — `paper_fts.year` missing), so the real user experience has always been CLI fallback anyway.
---
## P0/P1 matrix resolution
| Row | How Approach A fixes it |
|-----|------------------------|
| P0 R1: sql.js `paper_fts.year` | **Resolved by deletion.** No JS-owned SQL. Python owns the query next to the schema. |
| P0 R2: missing `--deep` flag | **Resolved.** Plugin passes `--deep` for `@` queries. One flag, one path. |
| P0 R3: `data.chunks` vs `matches` | **Resolved by unification.** Both search and retrieve return `data.matches` with stable field names. |
| P0 R5: delete-after-write bug | **Must fix independently.** Same Python build loop. Requires transaction-level fix. |
| P0 R4: `text` vs `matched_text` | **Resolved by unification.** One field name in the envelope. |
| P1 R6: resume gates on Chroma | **Must fix in build path.** Delete Chroma gating, check vec0 tables. |
| P1 R7: force deletes Chroma dir | **Must fix in build path.** Drop vec0 tables, not legacy dir. |
| P1 R8: dead PID stop unsettled | **Must fix in build path.** Cooperative cancellation + state settlement. |
| P1 R9: JSON vs SQLite split-brain | **Resolved.** Plugin reads `embed status --json` which queries live SQLite. JSON snapshot becomes debug-only. |
| P1 R10: meta-only health | **Must fix in status path.** Add vec0 queryability probe. |
---
## Result envelope — unified PFResult
All retrieval paths (M search, @ deep) return the same outer shape:
```json
{
"ok": true,
"data": {
"query": "knee",
"matches": [
{
"zotero_key": "...",
"title": "...",
"first_author": "...",
"year": 2024,
"journal": "...",
"domain": "...",
"abstract": "...",
"score": 0.95,
"text": "...",
"heading": "...",
"source": "fulltext"
}
]
},
"count": 5,
"warnings": []
}
```
Error envelope:
```json
{
"ok": false,
"error": {
"code": "VECTOR_CORRUPTED",
"message": "Vector index is unreadable. Rebuild vectors before retrieving.",
"details": {}
}
}
```
Error codes: `VECTOR_NOT_BUILT`, `VECTOR_CORRUPTED`, `MODEL_CHANGED`, `BACKEND_UNAVAILABLE`, `TIMEOUT`, `INTERNAL_ERROR`, `NO_PYTHON`.
---
## Build state flow
1. Plugin spawns `paperforge embed build --resume` (or `--force`).
2. Python writes `build_state` to SQLite as the only truth.
3. Plugin polls `paperforge embed status --json` periodically during build.
4. `embed status` reads live SQLite `build_state` and vec0 queryability, returns fresh PFResult.
5. Plugin renders progress bar and state from the status response.
6. On stop: plugin spawns `paperforge embed stop --json`. Python kills PID, writes `status=idle` to SQLite, returns settlement confirmation.
7. `vector-runtime-state.json` becomes a debug-only snapshot written by `embed status` for human inspection. Plugin never reads it as control-plane truth.
---
## Minimal implementation sequence
1. **Unify result envelope.** Make `paperforge search` and `paperforge retrieve` return the same `data.matches` key with the same field names (`first_author`, `text`). Add `--deep` flag plumbing to retrieve.
2. **Fix plugin parser.** Remove `matches`/`results`/`chunks` forking. Parse only `data.matches`. Remove `matched_text` check — use `text`.
3. **Fix plugin spawn.** Pass `--deep` for `@` queries. Delete sql.js service.
4. **Fix build path.** Transactional write-then-delete. Delete Chroma gating from resume/force. Add vec0 queryability check to status. Cooperative stop with state settlement.
5. **Fix plugin state.** Read live `embed status --json` instead of JSON snapshot. Poll during build.
6. **Add contract tests.** E2E: plugin spawn → CLI output → parse → render. Test every error code.
---
## Approximate files affected
- **Delete:** `paperforge/plugin/src/services/db.ts`, `paperforge/plugin/sql-wasm.wasm`
- **Modify plugin:** `dashboard.ts` (search spawn + parsing + state), `settings.ts` (build state), `memory-state.ts` (delete snapshot-as-truth), `python-bridge.ts` (unified spawn helper)
- **Modify Python:** `search.py` (unified envelope), `retrieve.py` (unified envelope + `--deep`), `embed.py` (fix build loop, Chroma cleanup, cooperative stop, status probe), `build_state.py` (canonical truth), `status.py` (vec0 queryability), `_chroma.py` (delete legacy production gates), `state_snapshot.py` (downgrade to debug-only)
- **New:** contract test file for envelope schema
---
## Comparison to Approaches B and C
| Dimension | A (CLI only) | B (sql.js cache) | C (worker) |
|-----------|-------------|-------------------|------------|
| Correctness risk | Lowest — one code path | Medium — staleness risk | Medium — IPC/lifecycle risk |
| Implementation complexity | Lowest | Medium | High |
| M search latency | ~330ms (debounce+spawn) | ~200ms (sql.js hit) | ~10-25ms (worker hit) |
| @ search latency | ~200-300ms | ~200-300ms | ~130ms + API |
| New IPC surface | None | None | JSON-lines protocol |
| Ownership clarity | Best — one owner | Good — two readers | Good — two workers |
| Upgrade path | Baseline | From A → B | From A → C |
| Files changed | ~12 | ~16 | ~22 + 4 new |
---
## Final verdict
**Approach A is the correct first recovery phase.** It restores retrieval correctness with the smallest diff and no new lifecycle complexity. It establishes the unified PFResult envelope and Python-as-canonical-owner contracts that both B and C also require. Once correctness is proven in the live vault with contract tests, the team can decide whether to add Approach B (sql.js read cache) or Approach C (panel-scoped worker) as a latency optimization.
**Bottom line: Implement Approach A now. Defer B and C until after correctness is restored and contract tests gate the live pipeline.**

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