Analysis updated 2026-05-18
Give a Claude-based agent framework (OpenClaw, NanoClaw, Biomni) a specific bioinformatics skill to load for a task.
Browse curated skills for genomics, proteomics, single-cell analysis, or other life sciences categories.
Reference standardized SKILL.md files describing when and how to invoke bioinformatics tools like samtools or MAFFT.
Build a modular AI agent pipeline for biomedical research without carrying every skill at once.
| biotender-max/awesome-bio-agent-skills | alexrosbach/replibook | arlandaren/proagents | |
|---|---|---|---|
| Stars | 25 | 25 | 25 |
| Language | Python | Python | Python |
| Setup difficulty | moderate | easy | easy |
| Complexity | 3/5 | 2/5 | 1/5 |
| Audience | researcher | ops devops | vibe coder |
Figures from each repo's GitHub metadata at analysis time.
Requires a compatible Claude-based agent framework (OpenClaw, NanoClaw, or Biomni) to actually use the skills.
Awesome Bio Agent Skills is a curated index of 1,676 reusable knowledge modules for AI agents working in biomedical research. The skills were gathered and deduplicated from 20 open-source repositories, then organized into 15 subject categories. Each entry is a self-contained folder with a standardized SKILL.md file, built to work with Claude-based agent frameworks such as OpenClaw, NanoClaw, and Biomni. The 15 categories span a wide range of life sciences tasks. Genomics is the largest, with over 500 skills covering whole-genome and whole-exome sequencing workflows, variant annotation, and genome assembly. Other categories include proteomics, single-cell analysis, transcriptomics, epigenomics, metagenomics, and protein design. There are also more utility-oriented categories for database queries, multi-omics data integration, bioinformatics command-line tools, visualization, and workflow orchestration. The skills are designed to be modular: an AI agent can load only the ones relevant to a given task rather than carrying all of them at once. Each skill folder describes what the skill does, when to use it, and how to invoke the relevant tools or libraries. The underlying tools referenced vary by category and include well-established bioinformatics software such as samtools, MAFFT, MACS3, and Biopython. The project follows the conventions of an awesome-list, a community format for collecting links and references to quality resources in a given field. It includes automated linting via GitHub Actions to keep entries consistently formatted. The license is CC0, meaning the contents are placed in the public domain. This repository is primarily useful to researchers or developers building AI agents that assist with bioinformatics analysis pipelines. It is not a standalone tool and does not run analyses itself. The full README is longer than what was shown.
A curated index of 1,676 reusable AI-agent skill modules for biomedical research, organized into 15 categories like genomics and proteomics.
Mainly Python. The stack also includes Python, Claude agents, samtools.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.