statistical-analysis
Pass
Audited by Gen Agent Trust Hub on Oct 24, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill instructions and documentation focus strictly on statistical methodologies and reporting standards without any malicious or deceptive prompts.
- [SAFE]: All identified Python dependencies (scipy, pingouin, statsmodels, pandas, matplotlib, seaborn, pymc, arviz) are well-known, reputable scientific libraries pinned to specific versions.
- [SAFE]: The bundled script
scripts/assumption_checks.pyperforms rigorous data validation and cleaning, including checks for finite values, non-missing data, and appropriate dimensions, which mitigates risks associated with malformed input data. - [SAFE]: External references and network requests are limited to documentation sites, official package repositories, and established academic services like arXiv and CrossRef.
- [SAFE]: No evidence of unauthorized file access, network exfiltration, persistence mechanisms, or privilege escalation attempts was found in the instructions or code.
Audit Metadata