# scikit

> scikit — achillesrasquinha-scikit. Use this tool when you need to integrate and analyze life science data from multiple sources, such as genomics, proteomics, and clinical trials, to inform AI-driven decisions in fields like drug discovery. It provides a unified interface to access and combine data from over 300 databases, streamlining data retrieval and analysis. Ideal for applications requiring comprehensive life science data integration, scikit enables seamless data exchange and collaboration via git.

Canonical page: https://skillsregistry.net/skills/achillesrasquinha-scikit  
JSON: https://api.skillsregistry.net/v1/skills/achillesrasquinha-scikit

## Description

A unified life science data layer for your AI agents - genomics, proteomics, drug discovery, clinical trials across 300+ databases.

## Trust

- **Trust score (0–1):** 0.89
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/achillesrasquinha/scikit)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "achillesrasquinha-scikit"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/achillesrasquinha-scikit` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/achillesrasquinha-scikit/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt