andy-stack_vaultkeeper-ai/Types/ExecutionStep.ts
Andrew Beal ab9ee08281 refactor: implement multi-agent orchestration architecture
Restructure the AI workflow from a single-agent model to a specialized
multi-agent system with distinct roles:

- Add AgentType enum (Main, Orchestration, Planning, Execution) to define
  agent specializations
- Replace AIControllerService and AIFunctionService with modular agent
  classes in Services/AIServices/:
  - MainAgent: Handles user interaction and delegates to orchestration
  - OrchestrationAgent: Coordinates plan execution and step-by-step workflow
  - PlanningAgent: Creates and revises execution plans
  - ExecutionAgent: Executes individual plan steps
  - AIController: Base class providing common agent loop functionality
- Create specialized prompts (OrchestrationPrompt, ExecutionPrompt) for
  agent-specific behavior
- Add OrchestrationResult type to communicate workflow control decisions
  (continue, abort, replan)
- Introduce agent-specific function scoping:
  - ExecuteWorkflow for main agent
  - CompleteTask for execution agent
  - CompleteStep/Replan/CancelPlan for orchestration agent
  - SubmitPlan/AskUserQuestionPlanning for planning agent
- Update BaseAIClass to use agentType property instead of isPlanningAgent
  boolean for model selection
- Simplify ExecutionPlan and ExecutionStep types by removing execution
  state tracking (moved to agent coordination)
- Remove PlanningEnabledAppendix and ExecutionStatus enum (superseded by
  agent architecture)
- Add comprehensive integration tests for agent workflows

This architecture provides better separation of concerns, clearer agent
responsibilities, and more robust plan execution with explicit orchestration
control flow.
2026-01-27 20:29:20 +00:00

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TypeScript

export interface ExecutionStep {
description: string;
instruction: string;
context?: string;
}