daymade
5c9eda4fbd
feat: optimize skills + add pipeline handoff chaining across 9 skills
...
asr-transcribe-to-text:
- Add local MLX transcription path (macOS Apple Silicon, 15-27x realtime)
- Add bundled script transcribe_local_mlx.py with max_tokens=200000
- Add local_mlx_guide.md with benchmarks and truncation trap docs
- Auto-detect platform and recommend local vs remote mode
- Fix audio extraction format (MP3 → WAV 16kHz mono PCM)
- Add Step 5: recommend transcript-fixer after transcription
transcript-fixer:
- Optimize SKILL.md from 289 → 153 lines (best practices compliance)
- Move FALSE_POSITIVE_RISKS (40 lines) to references/false_positive_guide.md
- Move Example Session to references/example_session.md
- Improve description for better triggering (226 → 580 chars)
- Add handoff to meeting-minutes-taker
skill-creator:
- Add "Pipeline Handoff" pattern to Skill Writing Guide
- Add pipeline check reminder in Step 4 (Edit the Skill)
Pipeline handoffs added to 8 skills forming 6 chains:
- youtube-downloader → asr-transcribe-to-text → transcript-fixer → meeting-minutes-taker → pdf/ppt-creator
- deep-research → fact-checker → pdf/ppt-creator
- doc-to-markdown → docs-cleaner / fact-checker
- claude-code-history-files-finder → continue-claude-work
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com >
2026-04-05 14:27:23 +08:00
daymade
6d261ce801
feat(deep-research): V6.1 source accessibility policy and Counter-Review Team
...
- Correct source accessibility: distinguish circular verification (forbidden)
from exclusive information advantage (encouraged)
- Add Counter-Review Team with 5 specialized agents (claim-validator,
source-diversity-checker, recency-validator, contradiction-finder,
counter-review-coordinator)
- Add Enterprise Research Mode: 6-dimension data collection framework
with SWOT, competitive barrier, and risk matrix analysis
- Update version to 2.4.0
- Add comprehensive reference docs:
- source_accessibility_policy.md
- V6_1_improvements.md
- counter_review_team_guide.md
- enterprise_analysis_frameworks.md
- enterprise_quality_checklist.md
- enterprise_research_methodology.md
- quality_gates.md
- report_template_v6.md
- research_notes_format.md
- subagent_prompt.md
Based on "深度推理" case study methodology lessons learned.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-04-04 09:15:17 +08:00
