pymc
Pass
Audited by Gen Agent Trust Hub on Jun 14, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: No security issues detected. The skill uses standard scientific Python libraries (PyMC, ArviZ, NumPy, Pandas, Matplotlib) for statistical modeling and data visualization.
- [SAFE]: All operations, including data ingestion from CSV files and the saving of model results in NetCDF or CSV formats, are local to the user's environment. No external network requests, exfiltration patterns, or hardcoded credentials were found.
- [SAFE]: The skill implements PyMC's modern API, which involves runtime compilation of computational graphs through the PyTensor library. This is the legitimate and expected behavior for high-performance Bayesian inference and does not present a security risk.
- [SAFE]: No evidence of prompt injection, code obfuscation, or persistence mechanisms was detected across the skill body, scripts, or documentation.
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