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dfine-semantic

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by dfine-io

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    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables coding agents to search a locally indexed repository and get back a token-budgeted deck of ranked code and doc snippets instead of a full-tree grep dump, with lexical, semantic, and prose-answering modes plus index status reporting. Runs fully offline for lexical queries and optionally uses an OpenAI-compatible provider for semantic or ask modes.
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables semantic and keyword search over a local codebase by chunking source files along function and class boundaries, embedding them offline, and fusing vector and BM25 results. Runs entirely on your machine in a single SQLite file, so AI coding agents can find relevant code with no API keys, telemetry, or cloud calls.
      7
      19 npm
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to find code by describing its behaviour rather than guessing file names, returning ranked file:line snippets that cost far fewer tokens than grep-then-read. Also surfaces neighbouring implementations, callers and tests around a location you already know, indexing local paths or git URLs locally on CPU.
      0
      1
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables local semantic code search across repositories using natural language, with AST-aware chunking and hybrid vector/FTS5 retrieval.
      -
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding assistants to search a codebase by meaning using locally generated embeddings, so relevant code is found even when terminology differs from the query, along with package version lookup, reindexing, cache reset, workspace switching, and status tools. Indexing runs progressively in the background with CPU throttling and a SQLite cache, letting searches work immediately on large projects.
      34 npm
      MIT

    TDQS

    A4.1/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: semantic_search retrieves code, index_project builds/refreshes the index, index_status reports state, and find_duplicates detects near-matches. There is no overlap between searching, indexing, status, and duplicate detection.

    Naming Consistency4/5

    All names use snake_case consistently, but the internal pattern varies slightly (adjective_noun, noun_verb, noun_noun, verb_noun). Still highly readable and predictable as a set.

    Tool Count4/5

    Four tools is lean but well-matched to a focused semantic-search-and-indexing server. Each tool earns its place without redundancy, though the surface is on the thin side.

    Completeness4/5

    The core lifecycle (index build, status, search, duplicate detection) is covered. Minor gaps exist, such as removing or clearing an index and per-file reindexing, but agents can work around these via index_project.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues