mmm-modeling

Pass

Audited by Gen Agent Trust Hub on Nov 2, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill instructions and reference files contain standard data science code patterns for Bayesian modeling using the pymc-marketing library.
  • [SAFE]: Data ingestion is limited to reading local CSV files via pandas, which is a standard and expected procedure for this use case.
  • [SAFE]: External references are directed toward the official documentation site (pymc-marketing.io) and the author's own GitHub repositories (github.com/pymc-labs/*), which are legitimate vendor resources.
  • [SAFE]: The skill uses well-known, established scientific Python libraries such as numpy, pandas, arviz, pymc, and scipy without any suspicious version pinning or installation patterns.
  • [SAFE]: No obfuscation, prompt injection, or persistence mechanisms were detected in the skill content. The use of standard NetCDF (.nc) files for saving and loading models is consistent with established practices in the PyMC ecosystem.
Audit Metadata
Risk Level
SAFE
Analyzed
Nov 2, 2026, 02:30 PM