clawbio

ClawBio

The first bioinformatics-native AI agent skill library.
Built on OpenClaw (180k+ GitHub stars). Local-first. Privacy-focused. Reproducible.

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Install in 30 seconds

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

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What ClawBio Does Today

87 skills (29 production-ready) + 8,000 Galaxy tools + 2,318 tests + benchmark validation. Local-first by default. Reproducible. No guessing.

v0.5.0 released (4 Apr 2026): Validation and Benchmark Infrastructure. AD ground truth benchmark, mock API server for offline testing, swappable fine-mapping pipeline (SuSiE vs ABF), 74 benchmark tests, red/green TDD mandate. Release notes. DOI: 10.5281/zenodo.19420648.

Snap a photo of a medication in Telegram. ClawBio identifies the drug from the packaging, queries your pharmacogenomic profile from your own genome, and returns a personalised dosage card — on your machine, in seconds:

Warfarin | CYP2C9 *1/*2 Intermediate · VKORC1 High Sensitivity AVOID — DO NOT USE · Standard dose causes over-anticoagulation in this genotype.

Or take any genetic variant (identified by its rsID — a unique label like rs9923231) and search nine genomic databases at once to find every known disease association, tissue-specific effect, and population frequency. Or estimate your genetic predisposition to conditions like type 2 diabetes by combining thousands of small-effect variants into a single polygenic risk score. Or explore the UK Biobank — a half-million-person research dataset — by asking in plain English what fields measure blood pressure, grip strength, or depression, and get back the exact field IDs, descriptions, and linked publications you need.

Many ClawBio analyses write a reproducibility/ bundle with replay commands, environment metadata, and output checksums. The exact files can vary by skill, and some replays still require the original external inputs to be present. See docs/reproducibility.md.

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Reference Genome