ml-ops-engineer
Pass
Audited by Gen Agent Trust Hub on Apr 1, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill follows security best practices for MLOps orchestration and does not contain any malicious patterns, prompt injections, or obfuscated content.
- [EXTERNAL_DOWNLOADS]: The skill documentation and examples reference well-known, industry-standard machine learning libraries and services, including MLflow, Feast, XGBoost, Scikit-learn, and FastAPI. It also uses official container registries (GCR) in its Kubernetes configuration examples.
- [COMMAND_EXECUTION]: Provides Python utility scripts for data drift analysis and model registry management. These scripts are implemented using the Python standard library and perform legitimate operations on local data files, consistent with the skill's stated purpose of MLOps engineering.
Audit Metadata