scikit-learn
Pass
Audited by Gen Agent Trust Hub on Nov 8, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides standard instructional content for using the scikit-learn library. Analysis of the scripts and reference documentation revealed no malicious patterns.
- [DYNAMIC_EXECUTION]: The reference documentation in
references/model_evaluation.mdcorrectly demonstrates the use ofpickleandjoblibfor model persistence. While these tools can execute arbitrary code if used on untrusted files, they are presented here as standard library features for local model saving and loading, which is a routine practice in machine learning workflows. - [EXTERNAL_DOWNLOADS]: The skill references several well-known and trusted Python packages for machine learning, including
scikit-learn,pandas,numpy,matplotlib,seaborn,imbalanced-learn,umap-learn, andcategory-encoders. These are standard industry-wide dependencies for data science and do not pose a security risk.
Audit Metadata