ClawBio Equity Scorer
PassAudited by VirusTotal on May 11, 2026.
Overview
Type: OpenClaw Skill Name: clawbio-equity-scorer Version: 0.1.0 The OpenClaw AgentSkills bundle 'clawbio-equity-scorer' is classified as benign. The `SKILL.md` provides clear, legitimate instructions for an AI agent to perform bioinformatics analysis, explicitly stating 'No data upload: All computation local. No external API calls for genomic data.' The `equity_scorer.py` script implements the described functionality using standard Python libraries (numpy, pandas, scikit-learn, matplotlib) for local file processing and computation. There is no evidence of data exfiltration, unauthorized command execution, persistence mechanisms, or malicious prompt injection attempts against the agent. File operations are confined to user-provided input and a designated output directory.
Findings (0)
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.