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 install for widely-used, reputable open-source packages including shap, matplotlib, numpy, pandas, scikit-learn, scipy, xgboost, lightgbm, tensorflow, torch, mlflow, and joblib. 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 mlflow for logging and joblib for model persistence represents standard industry practices for experiment tracking and model deployment.
Audit Metadata
Risk Level
SAFE
Analyzed
Nov 6, 2026, 12:15 PM