rawq: Local CLI Tool for AI Agent Semantic Code Search
What rawq does
rawq is a local CLI tool that helps AI agents find relevant code without reading entire files. It uses semantic search to guide AI agents to specific code parts instead of whole files, letting them use read/grep on the right files. The tool is not RAG nor a replacement for read/grep.
Technical implementation
rawq uses a 33MB local model by default that works via ONNX runtime for semantic search, combined with BM25 lexical search via tantivy. The tool supports tree sitter code chunking for 16 languages and works on any GPU thanks to ONNX with DirectML, CUDA, or CoreML, with automatic CPU fallback.
Performance and features
In testing, AI agents that were using rawq consumed 4x fewer tokens and completed tasks 2x faster compared to blind read/grep tools. rawq also has a map command that shows the structure of a codebase.
Development details
The tool is written in Rust, fully open-source, and released under MIT license. It's available on GitHub at https://github.com/auyelbekov/rawq.
📖 Read the full source: r/LocalLLaMA
👀 See Also
7-Agent System in Claude Code Replaces Sprint Ceremonies for Solo Devs
A PM-turned-solo-dev built a 7-agent team inside Claude Code that handles QA, PR review, security, architecture, and backlog grooming — all triggered by a single /review command.
OCTO-VEC: Open-source virtual software company with 24 AI agents
OCTO-VEC is an open-source TypeScript/SQLite project that simulates a software company with 9 default AI agents and 15 hirable specialists. It includes automated security scanning, per-agent git identities, and supports 22+ LLM providers.
Transloadit MCP Server Connects AI Agents to Media Processing Pipeline
Transloadit built an MCP server that connects Claude and other AI agents to their media processing pipeline with 86 Robots for video, audio, image, and document processing. Setup in Claude Code requires one line: npx -y @transloadit/mcp-server stdio with TRANSLOADIT_KEY and TRANSLOADIT_SECRET environment variables.
Replacing complex retrieval pipelines with simple git commands for AI agents
A developer replaced their 3GB Docker image with sentence-transformers, rank-bm25, and scikit-learn with a single tool that lets AI agents execute read-only shell commands like git log, grep, and git diff directly on their memory repository.