# vision-tagger

> vision-tagger — sagarjhaa-vision-tagger. Use this tool when you need to automatically tag and annotate images with accurate labels and metadata. The vision-tagger utilizes the Apple Vision framework to solve problems related to image recognition, object detection, and scene understanding, providing outputs such as classified images and annotated data. Ideal for macOS users working with image processing and computer vision tasks, it takes images as input and returns tagged and annotated images as output.

Canonical page: https://skillsregistry.net/skills/sagarjhaa-vision-tagger  
JSON: https://api.skillsregistry.net/v1/skills/sagarjhaa-vision-tagger

## Description

Tag and annotate images using Apple Vision framework (macOS only)

## 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/sagarjhaa-vision-tagger)

## 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": "sagarjhaa-vision-tagger"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sagarjhaa-vision-tagger` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sagarjhaa-vision-tagger/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