when-developing-ml-models-use-ml-expert
Pass
Audited by Gen Agent Trust Hub on Jun 18, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill implements a standard machine learning lifecycle, including data preprocessing, model selection, training, evaluation, and deployment. The code blocks use well-established Python libraries such as TensorFlow, Scikit-learn, and Pandas for their intended purposes.
- [EXTERNAL_DOWNLOADS]: The skill references standard machine learning dependencies and platform-specific tools like
claude-flowandflow-nexus. These references are transparent and align with the skill's objective of managing ML workflows. - [COMMAND_EXECUTION]: The skill involves routine file system operations such as reading datasets and writing model artifacts (e.g., .h5 files, evaluation reports). It also generates a static inference script for deployment purposes, which is a standard practice and does not involve executing untrusted code.
Audit Metadata