- Add GitHub Actions CI workflow (Python 3.10 and 3.12) - Add CI badge to README - Add ARCHITECTURE.md: pipeline overview, module table, schema, how to add a language extractor, security summary - Move eval reports from tests/ to worked/httpx/ and worked/mixed-corpus/ - Fix README: test count 163→212, language table (13 languages via tree-sitter), extract.py description, worked examples links benchmark: 8.8x token reduction on nanoGPT + minGPT + micrograd - Run AST extraction on 29 Python files across 3 Karpathy repos - 177 nodes, 246 edges, 17 communities (Leiden) - 8.8x avg token reduction vs naive full-corpus context stuffing - Notable: micrograd cleanly splits into engine/nn communities; nanoGPT model vs training loop correctly separated - Honest: stdlib import noise flagged, config isolates documented benchmark: 71.5x token reduction on mixed corpus (code+papers+images) Full run: nanoGPT+minGPT+micrograd + 5 research papers + 4 images 285 nodes, 340 edges, 53 communities Average BFS query: 1,726 tokens vs 123,488 naive (71.5x) Code-only (AST) sub-benchmark: 8.8x on 13k-word corpus
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Changelog
0.1.3 (2026-04-04)
- Fix:
pyproject.tomlstructure —requires-pythonanddependencieswere incorrectly placed under[project.urls] - Add: GitHub repository and issues URLs to PyPI page
- Add:
keywordsfor PyPI search discoverability - Docs: README clarifies Claude Code requirement, temporary PyPI name, worked examples footnote
0.1.1 (2026-04-04)
- Add: CI badge to README (GitHub Actions, Python 3.10 + 3.12)
- Add: ARCHITECTURE.md — pipeline overview, module table, extraction schema, how to add a language
- Add: SECURITY.md — threat model, mitigations, vulnerability reporting
- Add:
worked/directory with eval reports (karpathy-repos 71.5x benchmark, httpx, mixed-corpus) - Fix: pytest not found in CI — added explicit
pip install pyteststep - Fix: README test count (163 → 212), language table, worked examples links
- Docs: README reframed as Claude Code skill; Karpathy problem → graphify answer framing
0.1.0 (2026-04-03)
Initial release.
- 13-language AST extraction via tree-sitter (Python, JS, TS, Go, Rust, Java, C, C++, Ruby, C#, Kotlin, Scala, PHP)
- Leiden community detection via graspologic with oversized community splitting
- SHA256 semantic cache — warm re-runs skip unchanged files
- MCP stdio server —
query_graph,get_node,get_neighbors,shortest_path,god_nodes - Memory feedback loop — Q&A results saved to
.graphify/memory/, extracted on--update - Obsidian vault export with wikilinks, community tags, Canvas layout
- Security module — URL validation, safe fetch with size cap, path guards, label sanitisation
graphify installCLI — copies skill to~/.claude/skills/and registers inCLAUDE.md- Parallel subagent extraction for docs, papers, and images