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Graphify-Labs/graphify
Graphify gives coding agents a queryable project graph with provenance-tagged relationships, reducing repeated repository scans while keeping inferred links visibly distinct from extracted facts.
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Source Summary
Graphify maps code, documents, PDFs, images, and media into graph.html, GRAPH_REPORT.md, and graph.json. Code parsing is **local and LLM-free** through tree-sitter, while every edge is tagged **EXTRACTED, INFERRED, or AMBIGUOUS**.
Practical Implication
For large repositories, have agents use scoped graphify query and path calls before broad grep or repeated file reads. The graph preserves imports, calls, inheritance, rationale comments, document links, package dependencies, and cross-file paths without requiring embeddings.
Agent-Ready Context
Graphify maps code, documents, PDFs, images, and media into graph.html, GRAPH_REPORT.md, and graph.json. Code parsing is **local and LLM-free** through tree-sitter, while every edge is tagged **EXTRACTED, INFERRED, or AMBIGUOUS**. For large repositories, have agents use scoped graphify query and path calls before broad grep or repeated file reads. The graph preserves imports, calls, inheritance, rationale comments, document links, package dependencies, and cross-file paths without requiring embeddings. Documents and media need an assistant model or configured backend, so the fully local claim applies only to code extraction. Language and file support varies by optional package, and the supplied benchmark description does not include enough results here to judge retrieval quality.
Context Map
contextcodingdata#retrieval#context-engineering#skillsUncertainty
Documents and media need an assistant model or configured backend, so the fully local claim applies only to code extraction. Language and file support varies by optional package, and the supplied benchmark description does not include enough results here to judge retrieval quality.