# vtl-image-analysis

> vtl-image-analysis — rusparrish-vtl-image-analysis. Use this tool when you need to analyze the compositional structure of AI-generated images, as it measures visual elements using the Visual Thinking Lens (VTL) framework to solve problems in image understanding and generation. It takes AI-generated images as input and outputs compositional structure measurements, providing insights into visual balance and harmony. This tool is ideal for use cases where evaluating the aesthetic and visual coherence of generated images is crucial.

Canonical page: https://skillsregistry.net/skills/rusparrish-vtl-image-analysis  
JSON: https://api.skillsregistry.net/v1/skills/rusparrish-vtl-image-analysis

## Description

Measure compositional structure in AI-generated images using the Visual Thinking Lens (VTL) framework.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** media
- **Updated:** 2026-09-19

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/rusparrish-vtl-image-analysis)

## 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": "rusparrish-vtl-image-analysis"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/rusparrish-vtl-image-analysis` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/rusparrish-vtl-image-analysis/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