Why:
AI ambiguity scanning still inspected Markdown table rows when ignoreMarkdownTables was enabled, while replacement skipped those rows through centralized Markdown segmentation. That kept scanner and renderer semantics from fully matching.
What:
Route candidate occurrence scanning through segmentMarkdown protection, move table-row detection into the Markdown segment module, and add regressions for unlinked candidates, existing wikilinks, and AI requests inside ignored table rows.
Why:
The final architecture review found that AI ambiguity scanning and link replacement could diverge on scoped base-directory matching and raw Linear URL protection. The replacement renderer also still carried its own candidate traversal loop, which made that drift possible.
What:
Pass baseDir into ambiguity scanning, share raw URL protection across markdown segmentation and candidate scanning, and route replacement rendering through the scanner's single candidate-at-index matcher. Add regression coverage for baseDir scoped AI requests and Linear URL protection parity.
Why:
AI ambiguity requests were scanned without the current file path, so preventSelfLinking could not filter self-link candidates on the AI path.
What:
- Thread an optional filePath through resolveAmbiguities() and pass it into the shared candidate scanner.
- Pass the active markdown path without .md from the AI command in main.ts.
- Add a regression proving self-link candidates are skipped before AI requests are built when the current file matches.
Why:
- Task 1 still had drift between candidate scanning and Korean replacement special cases.
- The scanner could ask AI about Korean particle forms that replacement intentionally skips.
- The Korean suffix replacement path ignored resolved ambiguities and could apply a different target than the AI chose.
What:
- skip Korean particle trie hits in the Task 1 candidate scanner and ambiguity request path
- reuse a shared resolved-ambiguity link-content helper for the standard and Korean suffix replacement branches
- add Task 1 regressions and append the Task 1 fix report with focused and full verification results
Why:
- Existing wikilinks inside inline code were still being collected as candidate occurrences, which could drive resolveAmbiguities() to prepare AI work for text that replaceLinks() intentionally leaves untouched.
What:
- Added inline-code protected ranges to existing wikilink collection so matches inside backticks are ignored alongside the current block-level exclusions.
- Added regression coverage for scanCandidateOccurrences() and the resolveAmbiguities() request path.
- Appended the focused and full verification results to the task 1 report.
Why:
- Task 1 scanner drifted from replaceLinks in two places that affect AI ambiguity review.
- Trie-hit namespace handling was filtering candidate sets differently from replacement-time behavior.
- Protected-region scanning was still walking fenced code, callouts, and ignored headings that replaceLinks already shields.
What:
- make trie-hit scanning use the original candidate set and first-candidate scoped checks, matching current replaceLinks behavior
- skip fenced code blocks, callouts, and ignored headings before protected-regex scanning while preserving original occurrence offsets
- add regressions for trie-hit namespace semantics and protected-region skipping, plus AI-side coverage and append the fix report
Why:
- Candidate detection was duplicated between link replacement and AI ambiguity resolution, which made matching behavior hard to reason about.
- A single scanner improves locality for namespace, protected-span, case, and CJK matching rules.
What:
- Add a shared candidate scanner module for unlinked text and existing wikilinks.
- Route AI ambiguity request construction through the scanner.
- Keep link rendering behavior unchanged and covered by existing replacement tests.
- Implemented AI-powered link disambiguation using local LLMs (Gemma 4 / LM Studio).
- Refactored Trie and candidate mapping to support multiple link candidates per word.
- Added 'AI Link Enhancer' command with a progress bar UI in Obsidian.
- Enhanced link replacement logic to verify existing links and resolve ambiguities using context.
- Added comprehensive unit tests for AI disambiguation and candidate mapping.
- Updated settings to include AI configuration (endpoint, model, context length).
