scientific-visualization
Pass
Audited by Gen Agent Trust Hub on Mar 31, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: No prompt injection or adversarial instructions were found. The documentation and code examples focus exclusively on scientific plotting best practices and journal requirements.
- [SAFE]: The skill relies on standard, reputable scientific Python packages (matplotlib, seaborn, plotly, numpy, pandas, scipy). No suspicious dependencies or unpinned versions from unknown sources were identified.
- [SAFE]: No data exfiltration or credential theft patterns were detected. File operations are limited to saving figure exports (PDF, PNG, TIFF) to the local project directory using standard library functions.
- [SAFE]: The Python scripts and markdown files are well-documented and transparent. No obfuscation, hidden payloads, or suspicious dynamic execution (e.g., eval, exec) were found.
Audit Metadata