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wu-yc/labclaw

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Repository Install

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Overview

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README

LabClaw – Operating Layer for LabOS (Stanford-Princeton AI Co-Scientists)

LabClaw is a skill library, not a monolithic software package. You can install the full collection or copy only the skill folders that match your research workflows.

Overview

LabClaw packages 240 production-ready SKILL.md files for biomedical AI workflows across biology, lab automation, vision/XR, drug discovery, medicine, data science, literature research, and scientific visualization. Each skill teaches an OpenClaw-compatible agent when to use a tool, how to call it, and what kind of output to produce.

The collection is designed for researchers who want a practical, modular skill layer instead of a generic prompt bundle. You can use it as a broad starter library, or cherry-pick only the subfolders relevant to your lab, team, or project.

At a Glance

Domain Skills Focus
🧬 Biology & Life Sciences 86 Bioinformatics, single-cell, genomics, proteomics, multi-omics, databases
👁️ Vision & XR 5 Hand tracking, 3D pose estimation, segmentation, egocentric vision
💊 Pharmacy & Drug Discovery 36 Cheminformatics, molecular ML, docking, target research, pharmacology, drug databases
🏥 Medical & Clinical 22 Clinical trials, precision medicine, oncology, infectious disease, medical imaging
⚙️ General & Data Science 54 Statistics, machine learning, data management, scientific writing, quality control
📚 Literature & Search 33 Academic search, biomedical databases, multi-source discovery, patents, grants, citations
📊 Visualization 4 Scientific visualization, matplotlib, seaborn, plotly, publication-ready figures

Representative Workflows

Workflow Example skills
Single-cell and spatial omics anndata, scanpy, tooluniverse-spatial-transcriptomics
Drug discovery and molecular design rdkit, diffdock, tooluniverse-drug-repurposing
Clinical and precision medicine clinical, tooluniverse-precision-oncology, clinicaltrials-database
Statistics, ML, and figure generation statistics, scikit-learn, scientific-visualization
Literature review and reporting pubmed-search, citation-management, scientific-writing

3-Second Quick Start

Just send the message to OpenClaw:

install https://github.com/wu-yc/LabClaw

Use Cases

In Lab (with XR):

Repository Layout

LabClaw/
├── README.md
├── README.zh-CN.md
└── skills/
    ├── bio/          # 86 skills: genomics, proteomics, single-cell, systems biology, databases
    ├── vision/       # 5 skills: hand tracking, 3D pose, segmentation, egocentric
    ├── pharma/       # 36 skills: cheminformatics, docking, target discovery, pharmacology
    ├── med/          # 22 skills: clinical research, precision medicine, oncology, imaging
    ├── general/      # 54 skills: statistics, ML, writing, reproducibility, quality control
    ├── literature/   # 33 skills: search, databases, grants, patents, citations
    └── visualization/ # 4 skills: scientific visualization, matplotlib, seaborn, plotly

These projects are especially relevant if you want to place LabClaw in the broader biomedical-agent ecosystem:

Repository Why it matters
openclaw/openclaw The main runtime that loads workspace skills and provides the skills platform, onboarding flow, and agent workspace model that LabClaw is designed to fit into.
mims-harvard/ToolUniverse A large AI-scientist tool ecosystem. LabClaw includes many tooluniverse-* skills across omics, drug discovery, clinical workflows, and literature research.
snap-stanford/Biomni A complementary biomedical AI agent project. LabClaw already includes a biomni skill, making Biomni a natural reference point for users exploring autonomous biomedical research agents.

Full Skill Catalog

The original catalog is preserved below, but grouped into collapsible sections to make browsing easier on GitHub.

Skill Format

Every SKILL.md follows a consistent structure:

# Skill Name
## Overview        — what this skill enables
## When to Use     — trigger conditions for the AI agent
## Key Capabilities — specific tools, APIs, parameters
## Usage Examples  — concrete code or workflow examples

Credits

Skills curated by Yingcheng (Charles) Wu, Jinglin Jian, Zhe Zhao at Le Cong Lab of Stanford & Mengdi Wang Lab at Princeton.

We really thank K-Dense for the support.

License

MIT License

Star History

View this README on GitHub

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Install

npx skillfish add wu-yc/labclaw