经 AI Skill Hub 精选评估,ClawBio 获评「强烈推荐」。这款Agent工作流在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 8.0 分,适合有一定技术背景的用户使用。
ClawBio 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
ClawBio 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:pip 安装(推荐)
pip install clawbio
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install clawbio
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/ClawBio/ClawBio
cd ClawBio
pip install -e .
# 验证安装
python -c "import clawbio; print('安装成功')"
# 命令行使用
clawbio --help
# 基本用法
clawbio input_file -o output_file
# Python 代码中调用
import clawbio
# 示例
result = clawbio.process("input")
print(result)
# clawbio 配置文件示例(config.yml) app: name: "clawbio" debug: false log_level: "INFO" # 运行时指定配置文件 clawbio --config config.yml # 或通过环境变量配置 export CLAWBIO_API_KEY="your-key" export CLAWBIO_OUTPUT_DIR="./output"
<p align="center"> <strong>The first bioinformatics-native AI agent skill library.</strong><br> Built on <a href="https://github.com/openclaw/openclaw">OpenClaw</a> (180k+ GitHub stars). Local-first. Privacy-focused. Reproducible. </p>
<p align="center"> <a href="https://github.com/ClawBio/ClawBio/actions/workflows/ci.yml"><img src="https://github.com/ClawBio/ClawBio/actions/workflows/ci.yml/badge.svg" alt="CI"></a> <a href="#quick-start"><img src="https://img.shields.io/badge/python-3.10+-blue?logo=python&logoColor=white" alt="Python 3.10+"></a> <a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-green" alt="MIT License"></a> <a href="https://clawhub.ai"><img src="https://img.shields.io/badge/ClawHub-87_skills-orange" alt="ClawHub Skills"></a> <a href="https://doi.org/10.5281/zenodo.19420648"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.19420648.svg" alt="DOI"></a> <a href="https://github.com/ClawBio/ClawBio/issues"><img src="https://img.shields.io/github/issues/ClawBio/ClawBio" alt="Open Issues"></a> <a href="https://clawbio.github.io/ClawBio/slides/"><img src="https://img.shields.io/badge/slides-London_Bioinformatics_Meetup-purple" alt="Slides"></a> </p>
---
Core dependencies are declared in pyproject.toml and pinned in uv.lock: biopython, pandas, numpy, scikit-learn, matplotlib, openai, pydeseq2, google-cloud-bigquery, google-auth, conda-lock, rocrate. Most skills run with just these.
uv sync installs everything in a reproducible virtual environment. To add or update a dependency, run uv add <package> (or edit pyproject.toml and re-run uv sync); commit the resulting uv.lock change.
Some skills have additional requirements:
| Skill | Extra dependency | Install |
|---|---|---|
| Metagenomics | Kraken2, RGI, HUMAnN3 | Conda (see skill README) |
| Methylation Clock | PyAging | pip install pyaging |
| scRNA Embedding | scvi-tools | pip install scvi-tools |
| Galaxy Bridge | BioBlend | pip install bioblend |
No Docker or Singularity required for core functionality. Skills that need external bioinformatics tools document their setup in their own SKILL.md.
---
python skills/galaxy-bridge/galaxy_bridge.py --run fastqc --input reads.fq.gz --output results/
pip install clawbio # Python 3.11+
clawbio run pharmgx --demo
Prefer conda? conda install -c bioconda clawbio.
Or use as a Python library:
from clawbio import run_skill, list_skills
result = run_skill("pharmgx", demo=True)
Or install as a Claude Code plugin: /plugin marketplace add ClawBio/ClawBio
Developing ClawBio or want all skills with full demo data? Work from a source checkout instead (uv recommended):
git clone https://github.com/ClawBio/ClawBio.git
cd ClawBio
uv sync # installs from pyproject.toml + uv.lock
uv run python clawbio.py run pharmgx --demo
---
<p align="center"> <img src="img/clawbio-demo.gif" alt="ClawBio GWAS Lookup demo — querying 9 genomic databases from the terminal" width="700"> </p>
---
python skills/soul2dna/soul2dna.py --demo
pip install clawbio # or: conda install -c bioconda clawbio
clawbio run pharmgx --demo
PharmGx demo runs in <2 seconds. Needs Python 3.11+. To develop ClawBio or get all skills with full demo data, work from a source checkout instead:
git clone https://github.com/ClawBio/ClawBio.git && cd ClawBio
uv sync # or: pip install -e .
uv run python clawbio.py run pharmgx --demo
Inside Claude Code:
/plugin marketplace add ClawBio/ClawBio
/plugin install clawbio
All skills are then available as agent-routable commands. Alternatively, clone the repo and open it as your working directory in Claude Code; the CLAUDE.md at the repo root teaches Claude how to route requests to skills automatically.
git clone https://github.com/ClawBio/ClawBio.git && cd ClawBio
uv sync # Python 3.11+ (installs dependencies)
uv run python clawbio.py run pharmgx --demo
Or use pip: pip install -e . && python clawbio.py run pharmgx --demo
```
That's ClawBio. The goal is to make replayable bioinformatics workflows straightforward when a skill ships demo data and helper-backed reproducibility outputs.
---
```bash
ClawBio is first and foremost a local bioinformatics skill library. You can execute it directly from the UNIX command line or through its Python module without any messenger or chat interface at all.
The OpenClaw-borrowed "magic" happens when an external LLM interprets a user's request and translates it into those local library or command-line calls. In other words, the LLM operates at the orchestration layer, while the biological data processing remains local, inspectable, and reproducible.
To experience that orchestration layer conversationally, ClawBio can be used through Telegram or Discord via RoboTerri, as a Claude Code skill, or through a self-hosted OpenClaw gateway with browser-based webchat. Of these options, the self-hosted OpenClaw gateway offers the strongest privacy story together with LLM-assisted interaction, because the LLM stays at the meta/orchestration level rather than operating on the underlying biological data themselves.
```
See CONTRIBUTING.md for the full submission process. Join the contributors community on Telegram: t.me/ClawBioContributors.
---
result = run_skill("pharmgx", demo=True)
---
ClawBio's demo data is built on a real, fully open human genome: the Corpasome. The 23andMe SNP chip (~600K variants) has been available since launch. Now, the project also ships subsets from a 30x Illumina whole-genome sequence (GRCh37), covering ~4M SNPs, ~600K indels, and structural variants (DEL, DUP, INV, BND, INS, CNVs). All data comes from a single individual (Manuel Corpas), licensed CC0, and published on Zenodo (doi:10.5281/zenodo.19297389). This dataset is provided for research and educational purposes only.
See docs/reference-genome.md for use cases, subsets, and citation details.
---
python tests/benchmark/mock_api_server.py & ```
74 benchmark tests at v0.5.0 baseline, all green. The public leaderboard now tracks 168 / 182 tests passing (92.3%) across 10 audited skills, up from 80 / 140 (57.1%) at the original audit. See benchmarks.html for the live leaderboard and CHANGELOG.md for full details.
---
python skills/galaxy-bridge/galaxy_bridge.py --demo ```
Cross-platform chaining: Galaxy VEP annotates variants → ClawBio PharmGx generates dosage report. Galaxy Kraken2 classifies reads → ClawBio metagenomics profiler. Neither can do this alone.
Built on BioBlend (Galaxy Python SDK). Developed in collaboration with the Galaxy ML SIG.
---
ClawBio ships demo data from a real, fully open human genome: the Corpasome (Manuel Corpas, CC0): - 23andMe SNP chip (~600K variants) - 30x Illumina WGS (~4M SNPs, ~600K indels, structural variants) - Published on Zenodo: doi:10.5281/zenodo.19297389
SOUL.md --> Soul2DNA --> .genome.json --> GenomeMatch --> Recombinator --> Gen-N offspring
(trait (compiler) (diploid loci) (M x F rank) (meiosis + (.genome.json
scores) mutation) with clinical
history)
ClawBio indexes 8,000+ bioinformatics tools from usegalaxy.org via the Galaxy Bridge skill. Search by natural language, inspect tool schemas, and execute remotely — all from the CLI.
```bash
高质量的生物信息学AI工作流
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
AI Skill Hub 点评:ClawBio 的核心功能完整,质量优秀。对于自动化工程师和运维人员来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | ClawBio |
| 原始描述 | 开源AI工作流:🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first。⭐987 · Python |
| Topics | bioinformaticsai-agentsgenomics |
| GitHub | https://github.com/ClawBio/ClawBio |
| License | MIT |
| 语言 | Python |
收录时间:2026-06-19 · 更新时间:2026-06-20 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
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