seaborn
Pass
Audited by Gen Agent Trust Hub on Mar 31, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill uses standard scientific Python libraries (Seaborn, Matplotlib, Pandas, NumPy, SciPy) for data analysis and visualization tasks, which are well-known and trusted in the developer community.
- [SAFE]: Demonstrates fetching example datasets from the official Seaborn GitHub repository, which is an expected behavior for this library and targets a well-known source.
- [SAFE]: The documentation covers common file operations like reading CSV data and saving plots as images or PDFs, all of which are primary functions for data visualization and are implemented using established library methods.
- [SAFE]: No signs of prompt injection, obfuscation, unauthorized privilege escalation, or persistence mechanisms were found across the skill's content.
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