ClawBio Equity Scorer
PassAudited by ClawScan on May 1, 2026.
Overview
This appears to be a purpose-aligned local genomic diversity reporting tool, but it processes sensitive ancestry/genetic data and installs unpinned Python packages.
This skill is reasonable to install if you intend to analyze local VCF or ancestry CSV files. Keep the input data and generated equity_report outputs private, review reports before sharing, and consider pinning or verifying the Python dependencies for reproducible installs.
Findings (2)
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
Future installs may receive different package versions than the author tested.
The skill installs external Python packages without exact pinned versions. These dependencies are expected for the bioinformatics/statistics purpose, but unpinned packages can change over time.
uv | package: biopython; uv | package: pandas; uv | package: scikit-learn; uv | package: matplotlib; uv | package: numpy
Install from trusted package sources and prefer a lockfile or pinned versions if reproducibility or supply-chain control is important.
Generated reports and tables may reveal sensitive population, ancestry, or genomic characteristics of a dataset.
The skill is designed to process sensitive genomic and ancestry data and persist derived summaries, figures, tables, and reproducibility artifacts locally.
Input Formats ... VCF File ... Genotype fields (GT) for multiple samples ... Ancestry CSV ... population or ancestry ... Write report ... Markdown with embedded figure paths, methods, and reproducibility block.
Use this only on data you are authorized to analyze, choose a private output directory, and avoid sharing generated reports unless they have been reviewed for privacy.