Tag and annotate images using Apple Vision framework (macOS only). Detects faces, bodies, hands, text (OCR), barcodes, objects, scene labels, and saliency re...
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Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install vision-taggerOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install vision-taggerβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/vision-tagger/π‘Extract and place the folder at the path above, then restart your agent.
Category
πDocuments & NotesPlatforms
What Vision Tagger can do for your AI workflow
Tag and annotate images using directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 1,279+ developers worldwide
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing Vision Tagger
Help me get started with Vision Tagger
Explains what Vision Tagger does, walks through the setup, and runs a quick demo based on your current project
Use Vision Tagger to tag and annotate images using Apple Vision framework (macOS only)
Invokes Vision Tagger with the right parameters and returns the result directly in the conversation
What can I do with Vision Tagger in my documents & notes workflow?
Lists the top use cases for Vision Tagger, with example commands for each scenario
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Vision Tagger extends your AI assistant with the ability to tag and annotate images using Apple Vision framework (macOS only). Detects faces, bodies, hands, text (OCR), barcodes, objects, scene labels, and saliency re... Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using Vision Tagger as its underlying capability.
Vision Tagger works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install Vision Tagger once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
Getting started with Vision Tagger takes about two minutes. Place the skill at `~/.claude/skills/vision-tagger/` (personal, all projects) or `.claude/skills/vision-tagger/` (project-specific), then restart your AI client. From that point, typing `/vision-tagger` in any conversation activates it, or the AI will use it on its own when it detects a relevant request.
Vision Tagger has been installed 1,279 times, making it one of the more actively used skills in the Documents & Notes category. The install rate suggests it solves a real, recurring need rather than a niche edge case. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/vision-tagger/ for personal use (all projects), or .claude/skills/vision-tagger/ for project-specific use. Restart your AI client, then invoke with /vision-tagger or let the AI discover it automatically.
Vision Tagger supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Vision Tagger is free to install. Check the repository for licensing information.
Tag and annotate images using Apple Vision framework (macOS only). Detects faces, bodies, hands, text (OCR), barcodes, objects, scene labels, and saliency re...
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