#436 · Primary category: AI Coding Assistants

ctx

agents ai-agents anthropic automation claude claude-code context-management developer-tools harness knowledge-graph llm llm-wiki mcp micro-skills obsidian real-time recommendation-engine skill-management skills wiki

Repo-aware recommendations for skills, agents, MCP servers, and model harnesses. Use your own inventory or the shipped 79,958-node graph with 68,494 skills, 467 agents, 10,790 MCPs, and 207 harnesses.

Project last updated:08/24/26

GitHub Stars

581

Forks

71

Contributors

5

License

MIT

Why we included this project

Deciding which skills, MCP servers, or agent harnesses to load for a repository is usually guesswork. ctx's CTX Fit command turns that into a test: it profiles your repo, builds representative tasks from your history, and runs candidate AI coding configurations against them in an isolated, network-disabled sandbox. The cheapest setup that reliably passes your own test command wins, chosen by a fixed rule (reliability floor first, then cost, then simplicity), so an LLM can explain a result but never decide it. That is useful for teams adopting AI coding tooling who want evidence over vendor claims and do not want to spend on configurations that do not fit their codebase. The free local profile is read-only and spends nothing, so trying it costs nothing, and the paid evaluation path hands you a reviewable diff or pull request before anything is applied.

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