# io.github.agenson-horrowitz/structured-data-validator

> Use this tool when you need to ensure the accuracy and consistency of structured data for AI agents, solving problems such as data inconsistencies and format incompatibilities. It validates, transforms, and normalizes input data, accepting structured data formats and outputting validated and normalized data. Ideal for use cases where reliable data exchange between AI systems is critical, such as data integration, machine learning, and natural language processing applications.

Canonical page: https://skillsregistry.net/skills/io-github-agenson-horrowitz-structured-data-validator  
JSON: https://api.skillsregistry.net/v1/skills/io-github-agenson-horrowitz-structured-data-validator

## Description

Validate, transform, and normalize structured data for AI agents.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.8
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.agenson-horrowitz%2Fstructured-data-validator)
- **Repository:** <https://github.com/agenson-tools/structured-data-validator-mcp>

## 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": "io-github-agenson-horrowitz-structured-data-validator"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-agenson-horrowitz-structured-data-validator` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-agenson-horrowitz-structured-data-validator/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