pymoo
Pass
Audited by Gen Agent Trust Hub on Nov 8, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides documentation and executable Python examples for the legitimate pymoo optimization framework. All external dependencies (pymoo, optuna, joblib, matplotlib, numpy, scipy) are well-known scientific libraries from trusted package registries.
- [SAFE]: No evidence of prompt injection, data exfiltration, or persistence mechanisms was found. The code demonstrates standard data science workflows, including parallel evaluation using Python's multiprocessing and joblib modules.
- [SAFE]: Metadata and instructional content are consistent with the claimed purpose of the skill.
Audit Metadata