meeting-analyzer

# Meeting Insights Analyzer > Originally contributed by [maximcoding](https://github.com/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: ``` { speaker: string, timestamp_sec: number | null, text: string }[] ``` 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, ...