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.py performs 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
Risk Level
SAFE
Analyzed
Oct 24, 2026, 10:01 PM