# screen-vision

> Use this tool when you need to automate tasks on macOS by extracting text from the screen using Optical Character Recognition (OCR) and leveraging the Vision Framework. It solves problems such as data entry, text extraction, and UI automation, allowing for efficient workflow optimization. The tool takes screenshots as input and outputs extracted text, enabling seamless automation of various tasks.

Canonical page: https://skillsregistry.net/skills/ls18166407597-design-screen-vision  
JSON: https://api.skillsregistry.net/v1/skills/ls18166407597-design-screen-vision

## Description

macOS Local OCR & Automation Tool using Vision Framework.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-05-15

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/ls18166407597-design-screen-vision)

## 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": "ls18166407597-design-screen-vision"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ls18166407597-design-screen-vision` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ls18166407597-design-screen-vision/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