statistical-analysis
Pass
Audited by Gen Agent Trust Hub on Jul 31, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides legitimate documentation and code examples for academic statistical research, including test selection, assumption checking, and APA-style reporting.
- [EXTERNAL_DOWNLOADS]: The skill utilizes well-known, trusted scientific Python libraries such as scipy, statsmodels, pingouin, pymc, and arviz. It also references authoritative resources like the APA Style Guide and Cross Validated.
- [COMMAND_EXECUTION]: Python code snippets demonstrate standard use of statistical modeling and visualization functions without any suspicious subprocess or system-level execution.
- [DATA_EXFILTRATION]: No patterns of sensitive data access or external network transmission were detected. The skill operates on user-provided data structures for analysis purposes only.
- [INDIRECT_PROMPT_INJECTION]: While the skill involves processing external data (dataframes), the instructions and provided workflows do not demonstrate vulnerabilities to prompt injection. It focuses on numerical analysis and structured reporting.
Audit Metadata