mmm-modeling
Pass
Audited by Gen Agent Trust Hub on Jun 14, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill follows established data science best practices using standard Python libraries (pandas, numpy, scipy, statsmodels, pymc).
- [SAFE]: Data processing is performed locally on user-provided datasets (CSV, Excel, Parquet) or via connected MCP tools. No unauthorized data exfiltration was detected.
- [SAFE]: The implementation includes comprehensive validation scripts (
data_validator.py,acid_test.py) that perform statistical integrity checks (Holt-Winters, Granger causality, VIF) to ensure model truthfulness. - [EXTERNAL_DOWNLOADS]: The skill uses Chart.js from a well-known CDN (jsDelivr) within its HTML reports for interactive visualizations. This is a standard and acceptable practice for rendering dashboards.
- [SAFE]: No obfuscation, prompt injection, or persistence mechanisms are present in the provided instructions or scripts.
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