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    • A
      license
      A
      quality
      A
      maintenance
      AI-powered code assistant that provides advanced search and discovery capabilities across GitHub and NPM ecosystems, helping users understand code patterns, implementations, and connections between repositories.
      13
      526 npm
      932
      TypeScript
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables AI agents to discover and evaluate GitHub repositories from natural-language feature descriptions, returning ranked adoption-grade candidates with evidence and quality signals.
      3
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      AST-aware semantic code search engine for AI agents, enabling code retrieval by intent with call-graph context and optional LLM enrichment.
      1
      MIT
    • A
      license
      A
      quality
      F
      maintenance
      Provides code repository indexing and semantic search capabilities, allowing natural language queries to find relevant code snippets with automatic incremental indexing and multi-language support.
      1
      8 npm
      359
      ISC
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables semantic code search across projects using AI embeddings to find code by meaning rather than just text matching. Provides fast intelligent search, symbol analysis, and code similarity detection with multi-language support.
      MIT

    TDQS

    C2.8/5.0

    Scored across 30 tools

    Disambiguation2/5

    Multiple tools have overlapping purposes with near-identical descriptions: genius.find_best vs genius.hunt, github.compare vs research.deep_compare, and code.reach vs code.understand are easy to confuse. While some descriptions contain differentiating details, several boundaries remain unclear enough that an agent could misselect.

    Naming Consistency3/5

    Most tools use dot-namespaced names (memory.recall, github.search_code, code.reach), but the pattern is broken by forge_discover/forge_describe and subcommands mix single words, verbs, and snake_case (e.g., research.archaeology vs research.deep_compare). Readable but not fully consistent.

    Tool Count2/5

    With 30 tools, this exceeds the 25+ threshold for 'too many'. Several tools are redundant variations (e.g., two 'find best implementations' tools, two comparison tools), suggesting the surface could be consolidated rather than each tool earning its place.

    Completeness4/5

    The surface covers code memory CRUD (store, recall, evolve, forget, link, related, stats), research chain lifecycle, GitHub search/retrieval, local code understanding, and implementation discovery. Minor gaps like local full-text code search or exact-ID memory retrieval are workable, but not fatal.

    Maintenance

    ActivityNo data
    ResponsivenessResponsive