ml4t-cpcv
Pass
Audited by Gen Agent Trust Hub on Sep 13, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill contains instructions and code snippets for performing combinatorial cross-validation on time-series data. It follows standard quantitative finance practices and does not include any commands for unauthorized file access, network exfiltration, or persistence.
- [SAFE]: All referenced libraries and dependencies, including 'ml4t-diagnostic', are consistent with the vendor identity ('ml4t') and are used appropriately within the context of model diagnostics and strategy evaluation.
- [SAFE]: The code examples utilize well-known, legitimate Python packages such as NumPy and scikit-learn to perform mathematical operations and model splitting.
Audit Metadata