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-marketinglibrary. - [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, andscipywithout 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