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Methodology

graphify

graphify — Methodology. adoption: Apache-2.0, PyPI package `graphifyy`; repository created April 3, 2026, 103 187 stars and 10 024 forks as of August 6, 2026; default branch v8, README in 33 languages · category: Open source skill presented by the site, distinct from the site itself · definition: Skill and CLI turning a multi-format project into a queryable knowledge graph: code parsed locally into a tree-sitter AST with no model, prose and images processed semantically, each edge labeled by provenance, no vector index

«Safi Shamsi» built graphify as a skill and CLI that turns a whole project into a traversable knowledge graph, invoked as `/graphify` from «Claude Code», Cursor, Codex, Gemini CLI and around fifteen other clients. Code is parsed locally into «tree-sitter» ASTs with no model in the loop, and every edge carries its provenance: `EXTRACTED` when it is explicit in the source, `INFERRED` when graphify resolved it. Published by «Graphify Labs» under Apache-2.0, the repository was created on 3 April 2026 and showed 103,187 stars and 10,024 forks on 6 August 2026.

The design refuses embeddings and a vector store. Clustering runs through «NetworkX» and the Leiden algorithm; coverage reaches SQL, Terraform, Apex, «MCP» configurations, package manifests, Office files, PDFs, images and locally transcribed video. `# WHY:` comments become nodes wired to the code they explain.

The benchmark picture is split. On LOCOMO, graphify leads recall@10 at 0.497 against 0.149 for supermemory and 0.048 for mem0, yet trails on QA accuracy at 45.3% versus 49.7%. On LongMemEval-S it matches a dense RAG at 76%. Graph build costs zero LLM credits, which locates the defensible advantage in cost and traceability rather than answer quality.

Then there is the drift. On the same day, «graphify.net», Shamsi's own showcase and directory, advertised "3.7k+ GitHub stars", declared MIT three times against the repository's Apache 2.0 `LICENSE`, and still pushed a "71.5× token reduction" figure retired with the v1 README. A tool vendor writing the comparison guide for its own category occupies the evaluation query first.

Type
Methodology
adoption
Apache-2.0, PyPI package `graphifyy`; repository created April 3, 2026, 103 187 stars and 10 024 forks as of August 6, 2026; default branch v8, README in 33 languages
category
Open source skill presented by the site, distinct from the site itself
definition
Skill and CLI turning a multi-format project into a queryable knowledge graph: code parsed locally into a tree-sitter AST with no model, prose and images processed semantically, each edge labeled by provenance, no vector index
relations
15
Cited in
2 fiches

Adoption measures

Neighborhood

tree-sitter Safi Shamsi graphify.net Graphify Labs algorithme de Leiden NetworkX commentaires d'inten… faster-whisper pour … GitNexus

→ uses

tree-sitter TECHNOLOGIE high confidence timeless Source ↗
algorithme de Leiden CONCEPT high confidence timeless Source ↗
NetworkX TECHNOLOGIE high confidence timeless Source ↗
faster-whisper pour transcrire vidéo et audio localement TECHNOLOGIE high confidence timeless Source ↗

← created

Safi Shamsi PERSONNE high confidence stable Source ↗

← references

graphify.net TECHNOLOGIE high confidence evolving Source ↗

← publishes

Graphify Labs ORGANISATION high confidence evolving Source ↗

← is part of

commentaires d'intention CONCEPT high confidence timeless Source ↗

→ converges with

GitNexus TECHNOLOGIE high confidence evolving

Cited in (2)