Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cacheforge-ai/cacheforge-skills --skill meeting-autopilotgit clone --depth 1 https://github.com/cacheforge-ai/cacheforge-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cacheforge-ai/cacheforge-skills/meeting-autopilot)<a href="https://agentmods.dev/skills/cacheforge-ai/cacheforge-skills/meeting-autopilot"><img src="https://agentmods.dev/badge/skills/cacheforge-ai/cacheforge-skills/meeting-autopilot.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00052 | $0.01265 |
| Opus 5 | $0.00026 | $0.00633 |
| Sonnet 5 | $0.00010 | $0.00253 |
| Haiku 4.5 | $0.00005 | $0.00127 |
Grade A, and why
meeting-autopilot scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **bash**, **jq**, **python3**, **curl** (typically pre-installed) How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
✈️ Meeting Autopilot
Turn meeting transcripts into structured operational outputs — NOT just summaries.
Activation
This skill activates when the user mentions:
- "meeting transcript", "meeting notes", "meeting autopilot"
- "action items from meeting", "meeting follow-up"
- "process this transcript", "analyze this meeting"
- "extract decisions from meeting", "meeting email draft"
- Uploading or pasting a VTT, SRT, or text transcript
Permissions
permissions:
exec: true # Run extraction scripts
read: true # Read transcript files
write: true # Save history and reports
network: true # LLM API calls (Anthropic or OpenAI)
Requirements
- bash, jq, python3, curl (typically pre-installed)
- ANTHROPIC_API_KEY or OPENAI_API_KEY environment variable
Agent Workflow
Step 1: Get the Transcript
Ask the user for their meeting transcript. Accept any of:
- A file path to a VTT, SRT, or TXT file
- Pasted text directly in the conversation
- A file upload
The skill auto-detects the format (VTT, SRT, or plain text).
Important: This skill does NOT do audio transcription. If the user has an audio/video file, suggest they use:
- Zoom/Google Meet/Teams built-in transcription
- Otter.ai or Fireflies.ai for recording + transcription
whisper.cppfor local transcription
Step 2: Get Optional Context
Ask for (but don't require):
- Meeting title — helps with email subject lines and report headers
- If not provided, the skill derives it from the filename or uses "Meeting [date]"
Step 3: Run the Autopilot
Save the transcript to a temporary file if pasted, then run:
bash "$SKILL_DIR/scripts/meeting-autopilot.sh" <transcript_file> --title "Meeting Title"
Or from stdin:
echo "$TRANSCRIPT" | bash "$SKILL_DIR/scripts/meeting-autopilot.sh" - --title "Meeting Title"
The script handles all three passes automatically:
- Parse — normalize the transcript format
- Extract — pull out decisions, action items, questions via LLM
- Generate — create email drafts, ticket drafts, beautiful report
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- CHANGELOG.md 1.7 KB
- LICENSE 1.0 KB
- README.md 5.2 KB
- scripts/common.sh 4.7 KB runs code
- scripts/extract-items.sh 7.4 KB runs code
- scripts/generate-outputs.sh 9.1 KB runs code
- scripts/meeting-autopilot.sh 7.4 KB runs code
- scripts/parse-transcript.sh 5.3 KB runs code
- SECURITY.md 4.2 KB
- templates/classification-prompt.md 683 B
- templates/extraction-prompt.md 2.2 KB
- templates/outputs-prompt.md 1.8 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 138 lines · 52 tokens per session scan A ddf8329a282a
meeting-autopilot is a skill published in the GitHub repository cacheforge-ai/cacheforge-skills (10 stars, last pushed 6mo ago), licensed MIT. It adds 52 tokens to every session and 1,265 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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