evaluating-ml-models

Pass

Audited by Gen Agent Trust Hub on Oct 2, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill provides educational content and Python code templates for machine learning evaluation workflows. It utilizes standard, well-known libraries such as scikit-learn for metrics and cross-validation, Optuna and Ray Tune for hyperparameter optimization, and MLflow and Weights & Biases for experiment tracking.
  • [SAFE]: All external links and documentation references target official domains of established open-source projects or reputable machine learning services (scikit-learn.org, optuna.readthedocs.io, docs.ray.io, mlflow.org, docs.wandb.ai).
  • [SAFE]: No evidence of prompt injection, data exfiltration patterns, credential exposure, or malicious command execution was found in the instructions or the provided reference files.
Audit Metadata
Risk Level
SAFE
Analyzed
Oct 2, 2026, 02:01 PM