3 Commits

Author SHA1 Message Date
Porun db66b8727b feat: add callflow HTML export with Mermaid architecture diagrams 2026-05-09 23:26:01 +01:00
Safi 5db8f7ce39 docs: update surprising connections description, test count
style: replace all em dashes with hyphens

fix: explain hidden .graphify/ folder in skill output and README

fix: rename .graphify/ to graphify-out/ so output is visible by default
2026-04-06 16:06:31 +01:00
Safi 64e07abd98 docs: CI, architecture guide, worked examples, README fixes
- 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
2026-04-06 16:06:31 +01:00