From b0ed7026dceb3aa0959191efc5f344609255d5af Mon Sep 17 00:00:00 2001 From: Ed_ Date: Tue, 5 May 2026 19:15:51 -0400 Subject: [PATCH] docs(conductor): Synchronize docs for track 'Tree-Sitter C/C++ MCP Tools' --- conductor/product.md | 2 +- conductor/tech-stack.md | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/conductor/product.md b/conductor/product.md index 89c9125..2575fda 100644 --- a/conductor/product.md +++ b/conductor/product.md @@ -41,7 +41,7 @@ For deep implementation details when planning or implementing tracks, consult `d - **Role-Scoped Documentation:** Automated mapping of foundational documents to specific tiers to prevent token bloat and maintain high-signal context. - **Tiered Context Scoping:** Employs optimized context subsets for each tier. Tiers 1 & 2 receive strategic documents and full history, while Tier 3/4 workers receive task-specific "Focus Files" and automated AST dependency skeletons. - **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 Targeted View) and "Context Amnesia" to provide workers only with the absolute minimum context required. Features an intelligent context aggregation engine utilizing **Hash-Based Caching (SHA256)** and LRU eviction to eliminate redundant processing. Employs **Tier-Level Aggregation Strategies** (`full`, `summarize`, `skeleton`) configured directly via Agent Personas, integrating high-tier AI sub-agents during the aggregation pass to generate succinct, high-signal summaries for both code and text files. Includes **Manual Skeleton Context Injection**, allowing developers to preview and manually inject file skeletons or full content into discussions via a dedicated GUI modal. Features multi-level dependency traversal and AST caching to minimize re-parsing overhead and token burn. +- **Strict Memory Siloing:** Employs tree-sitter AST-based interface extraction (Skeleton View, Curated View, and Targeted View) and "Context Amnesia" to provide workers only with the absolute minimum context required. Supports **Python, C, and C++** languages for structural extraction. Features an intelligent context aggregation engine utilizing **Hash-Based Caching (SHA256)** and LRU eviction to eliminate redundant processing. Employs **Tier-Level Aggregation Strategies** (`full`, `summarize`, `skeleton`) configured directly via Agent Personas, integrating high-tier AI sub-agents during the aggregation pass to generate succinct, high-signal summaries for both code and text files. Includes **Manual Skeleton Context Injection**, allowing developers to preview and manually inject file skeletons or full content into discussions via a dedicated GUI modal. Features multi-level dependency traversal and AST caching to minimize re-parsing overhead and token burn. - **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 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. diff --git a/conductor/tech-stack.md b/conductor/tech-stack.md index af0c747..315b9a0 100644 --- a/conductor/tech-stack.md +++ b/conductor/tech-stack.md @@ -44,6 +44,7 @@ - **StdioMCPServer:** Manages local MCP servers via asynchronous subprocess pipes (stdin/stdout/stderr). - **RemoteMCPServer (SSE):** Provides a foundation for remote MCP integration via Server-Sent Events. - **JSON-RPC 2.0 Engine:** Handles asynchronous message routing, request/response matching, and error handling for all external MCP communication. + - **AST-Based C/C++ Tools:** Provides `ts_c_get_skeleton`, `ts_cpp_get_skeleton`, `ts_c_get_code_outline`, and `ts_cpp_get_code_outline` for structural analysis of C/C++ codebases using tree-sitter. - **src/rag_engine.py:** Core RAG implementation managing the vector store lifecycle, chunking strategies (character-based and AST-aware), and multi-provider search. Integrates with **ChromaDB** for local persistence and provides a bridge for external MCP retrieval tools.