set-covering-problem
Pass
Audited by Gen Agent Trust Hub on Mar 16, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides legitimate optimization modeling for set covering problems with no evidence of malicious intent or harmful patterns.
- [EXTERNAL_DOWNLOADS]: Dependencies include standard, well-known Python libraries such as pulp, numpy, pandas, and matplotlib, which are trusted for scientific computing.
- [COMMAND_EXECUTION]: The provided Python code utilizes the PuLP library to interface with optimization solvers (e.g., CBC) to find solutions to linear programming models, which is the standard and intended functionality for this domain.
Audit Metadata