✨ Features
Phase 1: Feature Card System for /octo:extract
Implemented feature detection and scoping for large codebases (500K+ LOC, 1000+ files):
- Auto-Detection: Scans codebases using directory structure and keyword patterns
- Directory-based detection (features/, modules/, services/) with 90% confidence
- Keyword-based detection (auth, payment, user, etc.) with 70% confidence
- Feature merging (combines >50% overlapping features)
- Unassigned file tracking
- Interactive Feature Selection: Guided flow for choosing scope
- Auto-triggers for 500+ file codebases
- Visual feature cards with file counts and confidence scores
- Scope refinement (exclude tests, docs, custom patterns)
- No JSON knowledge required
- Feature Extraction: Scope-based token filtering
--feature <name>- Extract specific feature--detect-features- Auto-detect all features--feature-scope <json>- Custom scope (expert mode)
- Output Generation: Master feature index
features-index.json- Machine-readable indexfeatures-index.md- Human-readable documentationextract-all-features.sh- Batch extraction script
Core Implementation:
- FeatureDetector (390 lines) - Auto-detection engine
- FeatureScopedExtractor (132 lines) - Token filtering
- Feature index generators (220 lines)
- 36 comprehensive unit tests (100% passing)
Interactive Command Flows
Standardized interactive question patterns across commands:
- multi.md: Added cost awareness questions
- Confirms intent before multi-provider execution
- Informed consent for ~$0.02-0.08/query external API costs
- Exit paths ("tell me more", "use free providers only")
- Interactive Questions Guide: Best practices documentation
- Two-step execution pattern (Ask → Execute)
- Question design guidelines (2-4 options, clear descriptions)
- Real-world examples from 7 commands
- Implementation checklist and testing strategies
Documentation:
- PHASE1_PROGRESS.md - Implementation summary
- INTERACTIVE_QUESTIONS_GUIDE.md - Command development best practices
- Updated extract.md with feature selection flows
- 7 commands now follow consistent interactive pattern
📊 Testing
- 36/36 feature detection tests passing ✅
- 114/120 total tests passing (6 pre-existing failures in pipeline.test.ts)
- 90%+ code coverage for new features
🎯 Impact
- Lower barrier to entry for feature extraction
- No manual JSON configuration needed
- Consistent UX across all complex commands
- Informed consent for costly operations
- Scalable extraction for large codebases