varunreddy/SkillMesh
A retrieval-gated skill architecture for LLM agents that scales to hundreds of tools by exposing only the top-K relevant capabilities per request.
Uses BM25 sparse + dense vector retrieval with reciprocal rank fusion to score and select the top-K most relevant tool cards from a registry, then injects only those into the agent prompt. Integrates directly with Claude via MCP server (`uvx` one-liner), Codex skill bundles, and local CLI workflows—all supporting standardized OpenAI function schemas. Includes role-based card grouping (e.g., `Data-Analyst`, `AWS-Engineer`) for multi-domain workflows, reducing prompt bloat from 50K+ tokens (full catalog) to ~3K (retrieval-selected cards).
Available on PyPI.
Stars
4
Forks
3
Language
Python
License
MIT
Category
Last pushed
Mar 04, 2026
Monthly downloads
118
Commits (30d)
0
Dependencies
5
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/mcp/varunreddy/SkillMesh"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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