mlops-observability
Pass
Audited by Gen Agent Trust Hub on May 3, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill serves as a best-practices guide and does not contain any executable scripts, shell commands, or automation logic that could be exploited.
- [SAFE]: References standard, well-known Python libraries (MLflow, SHAP, Evidently, DVC, Plyer) and tools (Docker, uv, Just) for their intended technical purposes in MLOps workflows.
- [SAFE]: No evidence of prompt injection, obfuscation, data exfiltration, or persistence mechanisms was detected.
- [SAFE]: Mentions of alerting services like PagerDuty and Slack are provided as architectural examples for system monitoring, not as functional integration points for exfiltration.
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