Meeting Minutes Taker

Transform raw meeting transcripts into comprehensive, evidence-based meeting minutes through iterative review.

Quick Start

Pre-processing (Optional but Recommended):

• Document conversion: Use doc-to-markdown skill to convert .docx/.pdf to Markdown first (preserves tables/images)
• Transcript cleanup: Use transcript-fixer skill to fix ASR/STT errors if transcript quality is poor
• Context file: Prepare context.md with team directory for accurate speaker identification

Core Workflow:

1. Read the transcript provided by user
2. Load project-specific context file if provided by user (optional)
3. Intelligent file naming: Auto-generate filename from content (see below)
4. Speaker identification: If transcript has "Speaker 1/2/3", FIRST ask the user to label speakers on the source platform and re-export (see Step 1.5 Phase 0); infer from text only as a fallback
5. Multi-turn generation: Use multiple passes or subagents with isolated context, merge using UNION
6. Self-review using references/completeness_review_checklist.md
7. Present draft to user for human line-by-line review
8. Cross-AI comparison (optional): Human may provide output from other AI tools (e.g., Gemini, ChatGPT) - merge to reduce bias
9. Iterate on feedback until human approves final version

Intelligent File Naming

Auto-generate output filename from transcript content:

Pattern: YYYY-MM-DD-<topic>-<type>.md

Component	Source	Examples
Date	Transcript metadata or first date mention	2026-01-25
Topic	Main discussion subject (2-4 words, kebab-case)	api-design, product-roadmap
Type	Meeting category	review, sync, planning, retro, kickoff

Examples:

• 2026-01-25-order-api-design-review.md
• 2026-01-20-q1-sprint-planning.md
• 2026-01-18-onboarding-flow-sync.md