# vision2agent

> vision2agent — notzabir-vision2agent. Use this tool when you need to translate visual designs and voice commands into actionable AI implementations. Vision2agent solves the problem of manually coding AI agent tasks by allowing users to draw and speak their intent, streamlining the development process. It takes in visual drawings and voice inputs, outputting implemented AI agent tasks, ideal for rapid prototyping and development workflows.

Canonical page: https://skillsregistry.net/skills/notzabir-vision2agent  
JSON: https://api.skillsregistry.net/v1/skills/notzabir-vision2agent

## Description

Draw on your app. Speak your intent. Your AI agent implements it.

## Trust

- **Trust score (0–1):** 0.61
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/notzabir/vision2agent)

## 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": "notzabir-vision2agent"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/notzabir-vision2agent` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/notzabir-vision2agent/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