# labloop

> labloop — zeltrin-labloop. Use this tool when you need to automate continuous scientific discovery and experimentation, as it solves problems of manual research iteration and data analysis by creating persistent AI research loops. It takes in experimental data and outputs adapted and evolved research strategies, integrating with git for version control. Utilize labloop in contexts where rapid experimentation and AI-driven insight are crucial, such as scientific research and development.

Canonical page: https://skillsregistry.net/skills/zeltrin-labloop  
JSON: https://api.skillsregistry.net/v1/skills/zeltrin-labloop

## Description

Automate continuous scientific discovery with persistent AI research loops that adapt and evolve across experiments.

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-10-13

## Source

- **Source listing:** [GitHub](https://github.com/Zeltrin/labloop)

## 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": "zeltrin-labloop"
    }
  }
}
```

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