A multi-agent bioinformatics platform for analyzing single-cell RNA-seq, bulk RNA-seq, and literature mining through natural language.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install lobster-bio-use
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install lobster-bio-use using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Lobster AI is a comprehensive multi-agent bioinformatics framework designed to handle the complexities of biological data analysis. By leveraging Openclaw Skills, researchers can interact with specialized agents that automate tasks ranging from raw data quality control to advanced transcriptomic clustering. This skill bridges the gap between sophisticated bioinformatics pipelines and intuitive natural language commands, making high-level data science accessible to biologists and developers alike.
The system utilizes a supervisor agent to coordinate specialist experts in transcriptomics, proteomics, and genomics. Whether you are downloading datasets from GEO or generating publication-quality visualizations, this skill provides a unified interface for the entire research lifecycle, ensuring reproducibility and efficiency in every analysis session.
To integrate this into your environment and use Openclaw Skills effectively, follow these installation steps:
# Install on macOS or Linux
curl -fsSL https://install.lobsterbio.com | bash
# Install via uv for full capability
uv tool install 'lobster-ai[full,anthropic]' && lobster init
# Verify configuration
lobster config-test
Ensure you have configured your API keys during the lobster init phase to enable agent communication.
The skill organizes research data within a .lobster_workspace/ directory using the following taxonomy:
| File Type | Description |
|---|---|
.h5ad |
Processed AnnData objects containing single-cell expression data |
.html |
Interactive visualizations and reports for browser-based review |
.png |
Publication-ready static plots and charts |
.csv |
Tabular data exports, such as marker gene lists and DE results |
.json |
Metadata and session provenance records |
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