meeting-autopilot
v0.1.2Turn meeting transcripts into operational outputs — action items, decisions, follow-up email drafts, and ticket drafts. Not a summarizer. An operator. Accept...
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byTodd Kuehnl@tkuehnl
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
The skill's name/description (turn transcripts into action items, emails, tickets) matches the actual behavior: the scripts parse transcripts, call an LLM, and generate reports. However the registry metadata at the top claimed no required environment variables or credentials, while SKILL.md and the scripts clearly require ANTHROPIC_API_KEY or OPENAI_API_KEY and binaries (jq, python3, curl). That metadata omission is an incoherence that could mislead users about what secrets are needed.
Instruction Scope
The SKILL.md and scripts are focused on parsing transcripts, calling the configured LLM, generating a Markdown report, and saving extracted items to ~/.meeting-autopilot/history/. The instructions and code do not attempt to read unrelated system files, contact third-party endpoints beyond the configured LLM API (Anthropic/OpenAI), or execute eval-style constructs. The scripts validate API URL schemes and use safe JSON construction (jq, stdin to Python) as documented.
Install Mechanism
There is no remote install/download declared (no installer spec), so nothing is fetched from arbitrary URLs. The skill ships multiple executable scripts (bash + small python snippets) which will run on the host when invoked. That is higher surface than a pure doc-only skill but there is no evidence of downloads or obfuscated payloads in the provided files.
Credentials
Requiring an LLM API key (ANTHROPIC_API_KEY or OPENAI_API_KEY) is proportionate to the stated functionality. However the registry metadata listed zero required env vars/primary credential, which conflicts with SKILL.md and the scripts. The skill also creates/stores history under the user's home directory (~/.meeting-autopilot/history/) which is documented and can be skipped with --no-history, but the presence of persistent local storage is a privacy consideration users should be aware of.
Persistence & Privilege
The skill writes extracted items to ~/.meeting-autopilot/history/ by default (and offers --no-history). It is not always:true and does not modify other skills or system-wide agent configs. Local persistence is expected for cross-meeting tracking, but users should be aware that extracted items (which may contain sensitive snippets) are stored on disk.
Scan Findings in Context
[no_pre-scan-findings] expected: Pre-scan reported no injection signals. This is consistent with the code, which uses jq and stdin-to-Python patterns and avoids eval/command substitution on user-controlled data.
What to consider before installing
What to consider before installing/running this skill:
- Metadata mismatch: The registry metadata lists no required env vars, but the skill requires ANTHROPIC_API_KEY or OPENAI_API_KEY (and optional ANTHROPIC_API_URL/OPENAI_API_URL). Treat the metadata omission as an error — assume an API key is required.
- Secrets: Only provide an LLM API key with appropriate scope and billing controls. Prefer a dedicated/limited API key for testing and rotate it after use if you are concerned.
- Sensitive transcripts: Transcripts are sent to the configured LLM provider. Do not process highly confidential meetings unless your organization's data policy allows sending that content to the chosen provider.
- Local history: The skill saves extracted items (not full transcripts) under ~/.meeting-autopilot/history/. Use --no-history to avoid persistent storage, or inspect/delete the directory if needed.
- Review and test in a sandbox: Because the package contains executable scripts, review the scripts (you have them) and run the tool in an isolated environment or VM if you are cautious.
- Confirm endpoints: The scripts only call the configured OpenAI or Anthropic endpoints and validate http(s) scheme. If you plan to use a proxy/custom URL, verify the custom URL before use.
- If you need higher assurance: ask the publisher to correct the registry metadata to declare required env vars and dependencies, and to provide a signed release or a vetted package from a known source.
What would change this assessment: if the registry metadata is corrected to declare the required API keys and binaries (resolving the inconsistency), and/or if independent provenance (a trusted homepage or repo with signed releases) is provided, I would raise confidence and likely mark the skill as benign. Conversely, discovery of any hidden network calls, telemetry, or attempts to access unrelated system credentials would move the verdict toward malicious.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.
