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    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding agents to keep persistent, verifiable memory of a codebase, including the reasons behind code, prior rejected approaches, and invariants, anchored to the code and carried along as the code moves.
      -
    • A
      license
      A
      quality
      A
      maintenance
      One local memory every coding agent on your machine shares — Claude Code, Cursor, Claude Desktop, OpenCode. Answers from past sessions, commits, CLAUDE.md/AGENTS.md and ADRs with the exact source, and withholds work another agent has claimed so two agents don't rewrite the same thing.
      4
      3
      81 PyPI
      1
      MIT
    • A
      license
      A
      quality
      C
      maintenance
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      10
      40 npm
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    • A
      license
      Not graded
      quality
      C
      maintenance
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    • A
      license
      Not graded
      quality
      A
      maintenance
      A local-first memory for AI coding agents. AgentRecall turns the feedback and failures you run into while coding into reusable rules, then serves the right ones back — on the command line or directly to Claude Code over MCP. Everything stays on your machine: no cloud sync, no web UI, no API keys.
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    TDQS

    A4.7/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool has a distinct trigger and output: find is repo-wide discovery, gs is drill-down into a known file, kb_search is fuzzy concept lookup, kb_lookup is exact-path lookup before edits, and kb_write/status/repair/repair_aliases each own a separate notebook lifecycle concern. The superficially similar pairs (kb_search/kb_lookup and kb_repair/kb_repair_aliases) are explicitly contrasted in their descriptions.

    Naming Consistency4/5

    The kb_* tools share a clean, predictable prefix and snake_case convention, and find is a readable imperative. gs is an opaque abbreviation that does not fit the pattern, but it is a single isolated exception rather than a systemic inconsistency.

    Tool Count5/5

    Eight tools is well-scoped for a code-intelligence-plus-notebook server: two navigation/analysis tools and six notebook read/write/maintenance tools. Every tool addresses a concrete workflow step, and the count sits comfortably in the ideal 3-15 range.

    Completeness5/5

    The notebook surface is fully covered: create/read/update/delete via kb_write, fuzzy search, exact-path lookup, status, and two repair paths for notes that become unreachable or stale. find and gs cover discovery and structural drill-down, and the only omitted action (git publishing) is intentionally documented as human-only.

    Maintenance

    ActivityActive
    ResponsivenessResponsive