Vision Analyze empowers AI agents to describe, compare, and extract structured data from images using multimodal vision models.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install image-vision
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install image-vision using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Vision Analyze?
Vision Analyze is a powerful tool within the Openclaw Skills library designed to bridge the gap between visual data and actionable insights. By leveraging multimodal AI models, this skill enables agents to interpret visual content with high accuracy, whether it is identifying objects, reading handwritten text, or analyzing complex data visualizations.
This skill is essential for developers building automated workflows that require visual understanding. It transforms raw pixels into structured information, allowing for seamless integration of visual media into broader text-based processing pipelines. By using Openclaw Skills like this one, users can automate document processing, UI debugging, and accessibility enhancements with minimal configuration.
Vision Analyze Use Cases
- Extracting structured data from receipts, business cards, and forms.
- Performing Optical Character Recognition (OCR) on screenshots or scanned documents.
- Describing visual content to improve web accessibility for visually impaired users.
- Comparing "before and after" images to detect specific changes or progress.
- Analyzing technical charts, graphs, and diagrams for data-driven insights.
- Monitoring content moderation by identifying inappropriate visual elements.
How Vision Analyze Works
- The user provides an image path or a list of image paths (supporting JPG, PNG, GIF, and WebP).
- A specific natural language prompt is attached to the image data to define the analysis goal.
- The skill passes the visual input to a multimodal model within the Openclaw Skills framework.
- The model processes the visual features and correlates them with the provided text instructions.
- The agent returns a detailed text description or structured JSON output based on the visual analysis.
Vision Analyze Setup
To get started with Vision Analyze, ensure your environment is configured for Openclaw Skills. You can invoke the vision capabilities directly via the agent's image interface.
# No separate installation required if Openclaw core is installed
# Simply ensure your multimodal model provider is configured
openclaw skill enable vision-analyze
Vision Analyze Data Schema & Taxonomy
Vision Analyze handles visual data and metadata through a streamlined taxonomy. It supports batch processing for up to 20 images in a single request.
| Attribute | Specification |
|---|---|
| Supported Formats | JPG, PNG, GIF, WebP |
| Input Type | File Path or URL |
| Max Images | 20 images per prompt |
| Output Format | Markdown Text or Structured JSON |
| Processing | Automatic resizing for large files |
Vision Analyze Advanced Features
- Multi-image comparison for identifying delta changes between visual states.
- Zero-shot OCR capable of reading complex layouts like restaurant menus and technical forms.
- Context-aware visual Q&A for debugging UI screenshots and error messages.
- Seamless integration with other Openclaw Skills to trigger text-based workflows from visual triggers.
- High-speed processing with automatic image optimization and resizing for latency reduction.
SKILL.md
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