bio-workflows-scrnaseq-pipeline
Pass
Audited by Gen Agent Trust Hub on Aug 15, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill follows established bioinformatics best practices for processing single-cell RNA-seq data. Instructions and code examples focus on data loading, quality control, normalization, and clustering.
- [COMMAND_EXECUTION]: Code snippets in R and Python perform standard file system operations restricted to the local working directory (e.g., reading count matrices and writing result files). There are no instances of arbitrary or dangerous command execution.
- [EXTERNAL_DOWNLOADS]: The documentation references well-known and reputable bioinformatics repositories, including 10x Genomics, the Human Cell Atlas, and the Gene Expression Omnibus (GEO), as sources for example datasets. These are documented neutrally as legitimate resources for the skill's primary purpose.
- [INDIRECT_PROMPT_INJECTION]: The workflow ingests external genomic data formats (HDF5, MTX). While these are external inputs, they are highly structured scientific data processed by specialized loaders (
Read10X,sc.read_10x_h5), presenting a negligible surface for prompt injection.
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