Val-sss 347b4ad976 feat: v1.0.0 — 5 meta-experts + 15 SKILL.md knowledge layer, architecture finalized ...

Meta-expert system (atomic capabilities, fixed):
  1. Locator — BM25+AST call graph code localization
  2. Generator — LLM code generation with domain knowledge injection
  3. Verifier — syntax check + pytest validation
  4. Debugger — runtime variable capture via sys.settrace
  5. Reviewer — requirement alignment check (LLM compares intent vs changes)

Knowledge layer (SKILL.md progressive disclosure, extensible):
  15 domain experts converted from YAML to SKILL.md directory format
  - Level 1 (Gate): name+keywords ~100 tokens/expert
  - Level 2 (Generator): full instructions loaded only for matched expert
  - Level 3 (on-demand): deterministic scripts, never enter LLM context

Key decisions based on 2025-2026 research:
  - Experts split by atomic capability, not business domain (arXiv:2604.09780)
  - Progressive disclosure prevents noise (Anthropic Agent Skills)
  - Only specific domain knowledge helps; generic rules hurt (SWE-Skills-Bench)
  - 5 atomic skills compose into all complex tasks (GitHub Copilot paper)

Changes:
  - Add kaiwu/experts/reviewer.py (Reviewer meta-expert)
  - Convert all 15 experts from .yaml to SKILL.md directories
  - Delete all .yaml expert files
  - Add CHANGELOG.md
  - Update README (meta-expert architecture, version badge)
  - Bump version to 1.0.0
  - 311 tests passing

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-29 19:35:24 +08:00

..

SKILL.md

feat: v1.0.0 — 5 meta-experts + 15 SKILL.md knowledge layer, architecture finalized

2026-04-29 19:35:24 +08:00