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meeting-minutes-taker

7.4

by daymade

117Favorites
272Upvotes
0Downvotes

Transforms raw meeting transcripts into high-fidelity, structured meeting minutes with iterative review for completeness. This skill should be used when (1) a meeting transcript is provided and meeting minutes, notes, or summaries are requested, (2) multiple versions of meeting minutes need to be merged without losing content, (3) existing minutes need to be reviewed against the original transcript for missing items, (4) transcript has anonymous speakers like "Speaker 1/2/3" that need identification. Features include: speaker identification via feature analysis (word count, speaking style, topic focus) with context.md team directory mapping, intelligent file naming from content, integration with transcript-fixer for pre-processing, evidence-based recording with speaker quotes, Mermaid diagrams for architecture discussions, multi-turn parallel generation to avoid content loss, and iterative human-in-the-loop refinement.

meeting-minutes

7.4

Rating

0

Installs

Business & Productivity

Category

Quick Review

Exceptional skill for transforming meeting transcripts into structured minutes. The description clearly covers all major capabilities (speaker identification, multi-turn generation, iterative refinement, diagram generation). Task knowledge is comprehensive with detailed workflows, concrete examples, and anti-patterns. The SKILL.md is well-structured with a clear quick-start guide, progressive workflow checklist, and organized sections, though it is quite lengthy (could benefit from more modularization). Novelty is high: the multi-turn parallel generation strategy with UNION merging, speaker identification via feature analysis, cross-AI comparison, and aggressive diagram inclusion are sophisticated techniques that would require significant tokens and expertise for a CLI agent to replicate. The integration with transcript-fixer and markdown-tools, plus human-in-the-loop iteration, demonstrates a mature understanding of real-world meeting documentation workflows. Minor deductions for structure due to the very detailed SKILL.md that could delegate more content to reference files.

LLM Signals

Description coverage9
Task knowledge10
Structure9
Novelty9

GitHub Signals

489
53
5
2
Last commit 0 days ago

Publisher

daymade

daymade

Skill Author

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daymade

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