Agent skill · AI & Agents

tooluniverse

Use this skill when working with scientific research tools and workflows across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery. This skill provides access to 600+ scientific tools including machine learning models, datasets, APIs, and analysis packages. Use when searching for scientific tools, executing computational biology workflows, composing multi-step research pipelines, accessing databases like OpenTargets/PubChem/UniProt/PDB/ChEMBL, performing tool discovery for research tasks, or integrating scientific computational resources into LLM work

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill scientific-pkg-tooluniverse-jackspace-claudeskillz-2 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 10 KB
Bundled scripts: none
Path: skills/ai-ml/scientific-pkg-tooluniverse-jackspace-claudeskillz-2/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# ToolUniverse ## Overview ToolUniverse is a unified ecosystem that enables AI agents to function as research scientists by providing standardized access to 600+ scientific resources. Use this skill to discover, execute, and compose scientific tools across multiple research domains including bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery. **Key Capabilities:** - Access 600+ scientific tools, models, datasets, and APIs - Discover tools using natural language, semantic search, or keywords - Execute tools through standardized AI-Tool Interaction Protocol - Compose multi-step workflows for complex research problems - Integration with Claude Desktop/Code via Model Context Protocol (MCP) ## When to Use This Skill Use this skill when: - Searching for scientific tools by function or domain (e.g., "find protein structure prediction tools") - Executing computational biology workflows (e.g., disease target identification, drug discovery, genomics analysis) - Accessing scientific databases (OpenTargets, PubChem, UniProt, PDB, ChEMBL, KEGG, etc.) - Composing multi-step research pipelines (e.g., target discovery → structure prediction → virtual scre

What's inside
Steps it walks through
  1. Overview
  2. When to Use This Skill
  3. Quick Start
  4. Basic Setup
  5. Model Context Protocol (MCP)
  6. Core Workflows
  7. 1. Tool Discovery
  8. 2. Tool Execution
  9. 3. Tool Composition and Workflows
  10. Scientific Domains
  11. Reference Documentation
  12. Example Scripts
  13. Best Practices
  14. Key Terminology
Ships with 1 file
  • metadata.json
Commands it runs
tooluniverse-smcp
More from claude-skill-registry
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About this skill
What does the tooluniverse skill do?

Use this skill when working with scientific research tools and workflows across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery. This skill provides access to 600+ scientific tools including machine learning models, datasets, APIs, and analysis packages. Use when searching for scientific tools, executing computational biology workflows, composing multi-step research pipelines, accessing databases like OpenTargets/PubChem/UniProt/PDB/ChEMBL, performing tool discovery for research tasks, or integrating scientific computational resources into LLM work

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill scientific-pkg-tooluniverse-jackspace-claudeskillz-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going