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    • F
      license
      A
      quality
      B
      maintenance
      Enables evaluating Python projects against a deterministic quality bar using analyzer findings, per-dimension scores, and a review verdict, exposed through MCP tools, resources, and prompts. Users can run evaluations, inspect rules, and list analyzers to assess code readiness for review.
      3
      -
    • A
      license
      Not graded
      quality
      D
      maintenance
      Code linting and style checking tools for AI agents, exposed as an MCP server. Supports style checks, naming conventions, complexity analysis, dead code detection, and import analysis.
      49 npm
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Lint agent SKILL.md files and MCP tool schemas to catch issues like missing descriptions, similar skills, unconstrained parameters, and destructive tools without confirmation gates.
      2
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Evaluates RAG outputs on faithfulness, answer relevancy, and context precision using an LLM-as-a-Judge backend. Exposes tools for running evaluations, scoring individual samples, and checking thresholds, enabling CI gating and on-demand assessment via MCP.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables LLM evaluation and observability by uploading documents, building test sets, running RAG pipelines, and automatically scoring answers for groundedness, hallucination risk, retrieval quality, latency, and cost, with tools exposed to MCP-compatible clients.
      1
      MIT