ml-classical-ml
Pass
Audited by Gen Agent Trust Hub on Jul 8, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill defines supervised and unsupervised learning pipelines using standard scikit-learn patterns such as Pipelines and ColumnTransformers.
- [SAFE]: It provides legitimate implementation examples for hyperparameter optimization using GridSearchCV, RandomizedSearchCV, and Optuna.
- [SAFE]: Security considerations documented in the skill appropriately address PII handling, model robustness, and serialized artifact security.
- [SAFE]: All identified dependencies are well-known, established machine learning and data science libraries, including scikit-learn, XGBoost, and LightGBM.
- [SAFE]: The extensive reference documentation, while containing repetitive boilerplate content across many files, does not contain hidden malicious instructions or obfuscated code.
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