# reprolith

> reprolith — clay-good-reprolith. Use this tool when you need to verify the accuracy and reliability of computational biomedical models by automatically rebuilding and re-running them to certify reproducibility. It solves problems of result validation and trustworthiness in the biomedical modeling literature by re-executing models and comparing outputs. It takes in existing models and produces certification reports as output, ideal for use in research and publication contexts where reproducibility is crucial.

Canonical page: https://skillsregistry.net/skills/clay-good-reprolith  
JSON: https://api.skillsregistry.net/v1/skills/clay-good-reprolith

## Description

Auto-reproduction & certification engine for the computational biomedical modeling literature — rebuild the model, re-run it, certify whether it reproduces its own results.

## Trust

- **Trust score (0–1):** 0.94
- **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/clay-good/reprolith)

## 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": "clay-good-reprolith"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/clay-good-reprolith` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/clay-good-reprolith/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