# STAMP

> Use this tool when you need to analyze solid tumor pathology data to identify associative models and patterns, solving problems in cancer research and diagnosis. STAMP takes in pathology data as input and outputs associative models, enabling researchers to gain insights into tumor behavior and progression. Ideal for use in cancer research and precision medicine applications, STAMP streamlines the analysis of complex tumor data.

Canonical page: https://skillsregistry.net/skills/katherlab-stamp  
JSON: https://api.skillsregistry.net/v1/skills/katherlab-stamp

## Description

Solid Tumor Associative Modeling in Pathology

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-05-22

## Source

- **Source listing:** [GitHub](https://github.com/KatherLab/STAMP)

## 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": "katherlab-stamp"
    }
  }
}
```

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