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meeting-analyzer

alirezarezvani/…e-skills

Analyzes meeting transcripts and recordings to surface behavioral patterns, communication anti-patterns, and actionable coaching feedback. Use this skill whenever the user uploads or points to meeting transcripts (.txt, .md, .vtt, .srt, .docx), asks about their communication habits, wants feedback on how they run meetings, requests speaking ratio analysis, mentions filler words or conflict avoidance, or wants to compare their communication across time periods. Also trigger when users mention tools like Granola, Otter, Fireflies, or Zoom transcripts. Even if the user just says "look at my meetings" or "how do I come across in meetings" — use this skill.

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安装命令

npx skills add https://github.com/alirezarezvani/claude-skills --skill meeting-analyzer

SKILL.md

Meeting Insights Analyzer

Originally contributed by maximcoding — enhanced and integrated by the claude-skills team.

Transform meeting transcripts into concrete, evidence-backed feedback on communication patterns, leadership behaviors, and interpersonal dynamics.

Core Workflow

1. Ingest & Inventory

Scan the target directory for transcript files (.txt, .md, .vtt, .srt, .docx, .json).

For each file:

  • Extract meeting date from filename or content (expect YYYY-MM-DD prefix or embedded timestamps)
  • Identify speaker labels — look for patterns like Speaker 1:, [John]:, John Smith 00:14:32, VTT/SRT cue formatting
  • Detect the user's identity: ask if ambiguous, otherwise infer from the most frequent speaker or filename hints
  • Log: filename, date, duration (from timestamps), participant count, word count

Print a brief inventory table so the user confirms scope before heavy analysis begins.

Meeting Insights Analyzer

Originally contributed by maximcoding — enhanced and integrated by the claude-skills team.

Transform meeting transcripts into concrete, evidence-backed feedback on communication patterns, leadership behaviors, and interpersonal dynamics.

Core Workflow

1. Ingest & Inventory

Scan the target directory for transcript files (.txt, .md, .vtt, .srt, .docx, .json).

For each file:

  • Extract meeting date from filename or content (expect YYYY-MM-DD prefix or embedded timestamps)
  • Identify speaker labels — look for patterns like Speaker 1:, [John]:, John Smith 00:14:32, VTT/SRT cue formatting
  • Detect the user's identity: ask if ambiguous, otherwise infer from the most frequent speaker or filename hints
  • Log: filename, date, duration (from timestamps), participant count, word count

Print a brief inventory table so the user confirms scope before heavy analysis begins.