Security audit
Security checks across malware telemetry and agentic risk
This looks like a safety guardrail, but it has conflicting packaged skill identities and can send sensitive tool-call details to LLM providers or logs with insufficient privacy scoping.
Review before installing. Use this only where sending evaluation inputs to configured LLM providers is acceptable, avoid passing secrets, payment details, private travel data, or sensitive shell commands unless redacted, prefer a trusted local endpoint for sensitive use, and ask the publisher to reconcile the agent-sentinel versus agent-eval-engine packaging and install paths.
headers={"Content-Type": "application/json"},
method="POST",
)
with urllib.request.urlopen(req, timeout=60) as r:
return json.loads(r.read().decode())["message"]["content"].strip()
except Exception as exc:64/64 vendors flagged this skill as clean.
No suspicious patterns detected.