meeting-transcripts

Capture meeting transcripts from Fireflies.ai via polling or webhooks. Auto-fetches transcripts, extracts action items/decisions/summaries, and writes structured markdown to memory. Use when user asks to check for meeting transcripts, set up meeting capture, or review past meetings. Supports cron-based polling (every 30 min) and real-time webhooks.

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Install skill "meeting-transcripts" with this command: npx skills add jessewunderlich/meeting-transcripts

Meeting Transcripts (Fireflies.ai)

Auto-capture meeting transcripts from Fireflies.ai, extract action items and decisions, write structured markdown to memory.

Setup

1. Store API key

echo "YOUR_FIREFLIES_API_KEY" > ~/.openclaw/secrets/fireflies-api-key.txt

Get your key from Fireflies dashboard → Settings → Developer Settings.

2. Poll for new transcripts (recommended)

node scripts/poll-new-meetings.js

Schedule via OpenClaw cron every 30 minutes. Tracks processed meetings to avoid duplicates.

3. Real-time webhooks (optional)

node scripts/webhook-server.js

Runs on port 3142. Expose via Cloudflare Tunnel or ngrok, then paste the URL into Fireflies Settings → Developer Settings → Webhook URL.

Optional webhook secret:

echo "YOUR_SECRET" > ~/.openclaw/secrets/fireflies-webhook-secret.txt

4. Fetch a specific transcript

node scripts/fetch-transcript.js <meetingId>

Output

Transcripts are saved to memory/meetings/YYYY-MM-DD-<title>.md with:

  • Title, date, duration, participants
  • AI summary from Fireflies
  • Action items (as checkboxes)
  • Key topics and keywords
  • Full transcript with speaker labels and timestamps

Cron Setup

Schedule polling every 30 minutes:

Check Fireflies for new meeting transcripts. Run: node <skill-path>/scripts/poll-new-meetings.js — if new meetings found, briefly notify the user with the meeting title(s). If no new meetings, do nothing (NO_REPLY).

Requirements

  • Fireflies.ai Pro account ($10/mo) — includes API access
  • Node.js 18+

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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