agent-based-modeling
Pass
Audited by Gen Agent Trust Hub on Sep 21, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill serves as a technical resource for designing and implementing agent-based simulations. It provides high-quality code examples for core ABM components such as agent architecture, environment design, and behavioral rules.
- [SAFE]: The code templates utilize standard, well-established libraries including NumPy and SciPy for spatial indexing (cKDTree), statistical analysis (KS-test), and optimization (differential evolution).
- [SAFE]: The 'validations' and 'sharp_edges' reference files promote best practices in simulation science, such as using reproducible random seeds and avoiding synchronization artifacts, which improves the robustness and reliability of the generated models.
- [SAFE]: No network operations, sensitive file access, command execution, or obfuscation techniques were detected across any of the provided files.
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