scanpy
Pass
Audited by Gen Agent Trust Hub on Jun 27, 2026
Risk Level: SAFEEXTERNAL_DOWNLOADSCOMMAND_EXECUTIONPROMPT_INJECTION
Full Analysis
- [SAFE]: The skill uses established scientific computing libraries including Scanpy, Pandas, NumPy, and Matplotlib to perform data analysis tasks.
- [EXTERNAL_DOWNLOADS]: Provides links to official Scanpy documentation and the scverse ecosystem tutorials. These references point to well-known, trusted resources within the bioinformatics community.
- [COMMAND_EXECUTION]: Includes Python scripts (scripts/qc_analysis.py) and templates (assets/analysis_template.py) that perform local file operations such as reading input datasets and writing results, plots, and metadata to user-specified directories.
- [PROMPT_INJECTION]: The skill processes user-supplied data files (e.g., .h5ad, .csv, .h5), which constitutes a theoretical surface for indirect prompt injection via metadata or feature names.
- Ingestion points: Data reading functions sc.read_h5ad, sc.read_10x_mtx, sc.read_10x_h5, and sc.read_csv found in SKILL.md, assets/analysis_template.py, and scripts/qc_analysis.py.
- Boundary markers: None present.
- Capability inventory: Local file writing via adata.write and to_csv; directory creation using os.makedirs.
- Sanitization: None implemented for natural language instructions embedded in scientific data structures.
Audit Metadata