pymoo
Pass
Audited by Gen Agent Trust Hub on Oct 1, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill serves as a reference and integration guide for the legitimate
pymoooptimization framework, focusing on numerical multi-objective and many-objective optimization. - [SAFE]: All identified dependencies, including
numpy,scipy,matplotlib,joblib, andoptuna, are widely recognized and trusted open-source packages in the Python data science ecosystem. - [SAFE]: The provided Python scripts demonstrate standard mathematical optimization workflows and include appropriate measures for environment reproducibility and parallel processing using standard libraries like
multiprocessingandjoblibwithout malicious behavior. - [SAFE]: No evidence of prompt injection, data exfiltration, obfuscation, or persistence mechanisms was found in the skill's instructions, code examples, or metadata.
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