statistical-analysis
Pass
Audited by Gen Agent Trust Hub on Sep 16, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTION
Full Analysis
- [SAFE]: The skill instructions and Python modules utilize standard scientific libraries for computation. No signs of obfuscation, hardcoded credentials, or malicious persistence mechanisms were found. External URLs provided are restricted to legitimate academic and documentation resources (e.g., APA Style, OSF, Stack Exchange).\n- [INDIRECT_PROMPT_INJECTION]: The skill involves the processing of external research data for statistical analysis, which creates a vulnerability surface for indirect prompt injection. However, the associated risks are minimal as the capabilities are focused on numerical processing.\n
- Ingestion points: Research data loaded into the
comprehensive_assumption_checkand related functions withinscripts/assumption_checks.py.\n - Boundary markers: No explicit data sanitization or boundary markers are defined for incoming datasets, relying on the agent's default data handling.\n
- Capability inventory: Statistical testing and visualization using
scipy.stats,statsmodels, andmatplotlib. No network requests or administrative file system operations are implemented.\n - Sanitization: Standard tabular data parsing and validation performed by the
pandasandnumpylibraries.
Audit Metadata