attune-help 0.7.0 — RAG-ready
Path-keyed summary sidecar + per-feature query fixtures + LLM polish pipeline. Makes attune-help the first retrieval-quality-tuned corpus in the ecosystem.
Retrieval benchmark (650 queries across 26 features)
| Metric | Before (0.5.1) | After (0.7.0) |
|---|---|---|
| Precision@1 | ~0% effective | 71.7% |
| Recall@3 | ~0% effective | 81.5% |
Clears the 70% P@1 gate from attune-ai's embeddings decision doc, deferring the fastembed v0.2.0 track.
What changed
templates/summaries_by_path.json— 124 polished path-keyed summaries (replaces silently-ignored feature-keyed schema for RAG consumers).templates/fixtures/*.yaml— 26 per-feature query fixtures for regression benchmarks.- Rolled forward 0.6.0's user-facing CLI (
attune-help lookup,list,search,simpler). - Development status: Beta (was Alpha).
Consumer action required
- attune-ai + attune-author: bump
attune-help>=0.5.1,<0.6to<0.8. - attune-rag 0.1.2: point
DirectoryCorpusatsummaries_by_path.json.
Known quality variance: 6 features below 60% P@1 (documented in CHANGELOG), scheduled for 0.7.1.