# croissant-validation

> croissant-validation — jettyio-croissant-validation. Use this tool when you need to validate MLCommons Croissant dataset metadata for schema compliance, solving issues with inconsistent or incorrect data formatting. It takes JSON-LD metadata as input and outputs validation results, providing a stateless service for ensuring data integrity. Ideal for use in machine learning workflows requiring standardized dataset metadata.

Canonical page: https://skillsregistry.net/skills/jettyio-croissant-validation  
JSON: https://api.skillsregistry.net/v1/skills/jettyio-croissant-validation

## Description

Validates MLCommons Croissant dataset metadata (JSON-LD) for schema compliance, as a stateless MCP server.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/huze53onwa)
- **Repository:** <https://github.com/jettyio/croissant-validation>

## 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": "jettyio-croissant-validation"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jettyio-croissant-validation` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jettyio-croissant-validation/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