shap
Pass
Audited by Gen Agent Trust Hub on Nov 6, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill serves as a legitimate educational resource for machine learning practitioners using the SHAP (SHapley Additive exPlanations) library.
- [EXTERNAL_DOWNLOADS]: The documentation includes standard installation instructions using
uv pip installfor widely-used, reputable open-source packages includingshap,matplotlib,numpy,pandas,scikit-learn,scipy,xgboost,lightgbm,tensorflow,torch,mlflow, andjoblib. These references are typical for the stated purpose of the skill. - [COMMAND_EXECUTION]: The skill provides numerous Python code snippets for common data science tasks such as model training, computing feature importance, and generating visualizations. These operations are performed using standard libraries within the user's environment.
- [DATA_EXPOSURE_AND_EXFILTRATION]: No sensitive file access, credential harvesting, or suspicious network operations were found. The use of
mlflowfor logging andjoblibfor model persistence represents standard industry practices for experiment tracking and model deployment.
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