Agent skill · writing content · alirezarezvani
meeting-analyzer
Use when the user shares meeting transcripts (.vtt, .srt, .txt, Otter, Granola, Zoom) or asks how they come across in meetings. Measures speaking ratio, filler words and avoidance patterns and gives coaching.
Why this skill is useful
Adds a comprehensive analysis workflow for meeting transcripts, including speaker dynamics and conflict detection that the AI cannot generate on its own.
What it needs
About 7k tokens when loaded. Last updated 2026-08-05. 23,939 stars on the source repository.
What this skill does
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. 2. Normalize Transcripts Different tools produce wildly different formats. Normalize everything into a common internal structure before analysis: Handling per format: VTT/SRT: Parse cue timestamps + text. Speaker labels may be inline (<v Speaker>) or prefixed. Plain text: Look for Name: or [Name] prefixes per line. If no speaker labels exist, warn the user that per-speaker analysis is limited. Markdown: Strip formatting, then treat as plain text. DOCX: Extract text content, then treat as plain text. JSON: Expect an array of objects with speaker/text fields (common Otter/Fireflies export). If timestamps are missing, degrade gracefully — skip timing-dependent metrics (speaking pace, pause analysis) but still run text-based analysis. 3. Analyze Run all applicable analysis modules below. Each module is independent — skip any that don't apply (e.g., skip speaking ratios if there are no speaker labels). …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills alirezarezvani/meeting-analyzer--4f455e