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 pymoo optimization framework, focusing on numerical multi-objective and many-objective optimization.
  • [SAFE]: All identified dependencies, including numpy, scipy, matplotlib, joblib, and optuna, 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 multiprocessing and joblib without 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.
Audit Metadata
Risk Level
SAFE
Analyzed
Oct 1, 2026, 07:50 AM
Security Audit — agent-trust-hub — pymoo