lr-tuning
Pass
Audited by Gen Agent Trust Hub on Jun 29, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill implements hyperparameter tuning using standard data science libraries including Optuna, scikit-learn, and XGBoost, with all operations performed locally.
- [SAFE]: Data ingestion is limited to local files (CSV/Parquet) provided by the user via command-line arguments, used solely for model training and evaluation.
- [SAFE]: No suspicious network activity, obfuscation techniques, or unauthorized privilege escalation attempts were detected.
- [SAFE]: The vendor structure for local dependency management is a standard and safe pattern used for modularizing skill code.
- [SAFE]: Model saving and report generation follow expected behavior for a model-tuning utility, with outputs directed to a user-defined or timestamped local directory.
Audit Metadata