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docs(conductor): Synchronize docs for track 'True Parallel Worker Execution'

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Edward R. Gonzalez
2026-03-06 16:56:31 -05:00
parent 7da2946eff
commit d7dc3f6c49
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conductor/product.md
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@@ -42,7 +42,8 @@ For deep implementation details when planning or implementing tracks, consult `d
- **Worker Spawn Interceptor:** A mandatory security gate that intercepts every sub-agent launch. Provides a GUI modal allowing the user to review, modify, or reject the worker's prompt and file context before it is sent to the API. - **Worker Spawn Interceptor:** A mandatory security gate that intercepts every sub-agent launch. Provides a GUI modal allowing the user to review, modify, or reject the worker's prompt and file context before it is sent to the API.
- **Strict Memory Siloing:** Employs tree-sitter AST-based interface extraction (Skeleton View, Curated View) and "Context Amnesia" to provide workers only with the absolute minimum context required, preventing hallucination loops. - **Strict Memory Siloing:** Employs tree-sitter AST-based interface extraction (Skeleton View, Curated View) and "Context Amnesia" to provide workers only with the absolute minimum context required, preventing hallucination loops.
- **Explicit Execution Control:** All AI-generated PowerShell scripts require explicit human confirmation via interactive UI dialogs before execution, supported by a global "Linear Execution Clutch" for deterministic debugging. - **Explicit Execution Control:** All AI-generated PowerShell scripts require explicit human confirmation via interactive UI dialogs before execution, supported by a global "Linear Execution Clutch" for deterministic debugging.
- **Parallel Tool Execution:** Executes independent tool calls (e.g., parallel file reads) concurrently using an asynchronous execution engine, significantly reducing end-to-end latency for complex AI turns. - **Parallel Multi-Agent Execution:** Executes multiple AI workers in parallel using a non-blocking execution engine and a dedicated `WorkerPool`. Features configurable concurrency limits (defaulting to 4) to optimize resource usage and prevent API rate limiting.
- **Parallel Tool Execution:** Executes independent tool calls (e.g., parallel file reads) concurrently within a single agent turn using an asynchronous execution engine, significantly reducing end-to-end latency.
- **Automated Tier 4 QA:** Integrates real-time error interception in the shell runner, automatically forwarding technical failures to cheap sub-agents for 20-word diagnostic summaries injected back into the worker history. - **Automated Tier 4 QA:** Integrates real-time error interception in the shell runner, automatically forwarding technical failures to cheap sub-agents for 20-word diagnostic summaries injected back into the worker history.
- **Detailed History Management:** Rich discussion history with branching, timestamping, and specific git commit linkage per conversation. - **Detailed History Management:** Rich discussion history with branching, timestamping, and specific git commit linkage per conversation.
- **In-Depth Toolset Access:** MCP-like file exploration, URL fetching, search, and dynamic context aggregation embedded within a multi-viewport Dear PyGui/ImGui interface. - **In-Depth Toolset Access:** MCP-like file exploration, URL fetching, search, and dynamic context aggregation embedded within a multi-viewport Dear PyGui/ImGui interface.

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conductor/tech-stack.md
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- **Taxonomy & Artifacts:** Enforces a clean root by organizing core implementation into a `src/` directory, and redirecting session logs and artifacts to configurable directories (defaulting to `logs/sessions/` and `scripts/generated/`). Temporary test data and test logs are siloed in `tests/artifacts/` and `tests/logs/`. - **Taxonomy & Artifacts:** Enforces a clean root by organizing core implementation into a `src/` directory, and redirecting session logs and artifacts to configurable directories (defaulting to `logs/sessions/` and `scripts/generated/`). Temporary test data and test logs are siloed in `tests/artifacts/` and `tests/logs/`.
- **ApiHookClient:** A dedicated IPC client for automated GUI interaction and state inspection. - **ApiHookClient:** A dedicated IPC client for automated GUI interaction and state inspection.
- **mma-exec / mma.ps1:** Python-based execution engine and PowerShell wrapper for managing the 4-Tier MMA hierarchy and automated documentation mapping. - **mma-exec / mma.ps1:** Python-based execution engine and PowerShell wrapper for managing the 4-Tier MMA hierarchy and automated documentation mapping.
- **dag_engine.py:** A native Python utility implementing `TrackDAG` and `ExecutionEngine` for dependency resolution, cycle detection, transitive blocking propagation, and programmable task execution loops. - **dag_engine.py:** A native Python utility implementing `TrackDAG` and `ExecutionEngine` for dependency resolution, cycle detection, transitive blocking propagation, and programmable task execution loops. Refined to decouple status management from dependency resolution to support external pool control.
- **multi_agent_conductor.py:** Orchestrates the concurrent execution of implementation tracks using a non-blocking `ConductorEngine` and a thread-safe `WorkerPool`. Employs configurable concurrency limits and thread-local context isolation to manage multi-agent state.
- **Thread-Local Context Isolation:** Utilizes `threading.local()` for managing per-thread AI client context (e.g., source tier tagging), ensuring thread safety during concurrent multi-agent execution. - **Thread-Local Context Isolation:** Utilizes `threading.local()` for managing per-thread AI client context (e.g., source tier tagging), ensuring thread safety during concurrent multi-agent execution.
- **Asynchronous Tool Execution Engine:** Refactored MCP tool dispatch and AI client loops to use `asyncio.gather` and `asyncio.to_thread`, enabling parallel execution of independent tool calls within a single AI turn to reduce latency. - **Asynchronous Tool Execution Engine:** Refactored MCP tool dispatch and AI client loops to use `asyncio.gather` and `asyncio.to_thread`, enabling parallel execution of independent tool calls within a single AI turn to reduce latency.