No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by jaechang-hits · Claude Skill · ★ 352
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is SciAgent-Skills safe to install? View the security audit →
SciAgent-Skills 196 ready-to-use scientific skills for AI coding agents — covering genomics, proteomics, drug discovery, biostatistics, scientific computing, and scientific writing. Each skill is a self-contained SKILL.md file with runnable code examples, key parameters, troubleshooting guides, and best practices. Designed for Claude Code, but compatible with any agent that reads markdown skill files. What's Inside Skill types: 72 toolkits, 53 database connectors, 36 guides, 35 pipelines Installation Prerequisites -
| Stars | 352 |
| Forks | 34 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 73.874389978355/100 |
| Open Issues | 6 |
| Last Updated | 2026-08-29 |
| Created | 2026-02-18 |
| Platforms | claude-code, python |
| Est. Tokens | ~15k |
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SciAgent-Skills is 197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, single-cell, drug discovery, proteomics, and more. Powers OmicsHorizon.. It is categorized as a Claude Skill with 352 GitHub stars.
SciAgent-Skills is primarily written in Python. It covers topics such as ai-agent, bioinformatics, biostatistics.
You can find installation instructions and usage details in the SciAgent-Skills GitHub repository at github.com/jaechang-hits/SciAgent-Skills. The project has 352 stars and 34 forks, indicating an active community.
The top alternatives to SciAgent-Skills on Agent Skills Hub include awesome-bio-agent-skills, k-dense-byok, wisp-science. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: