An AI-powered vision tool that provides detailed structural and contextual analysis of screenshots and images.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install screenshot-analyzer
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 screenshot-analyzer 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 Screenshot Analyzer?
The Screenshot Analyzer is a specialized utility designed to translate visual information into actionable technical insights. By utilizing vision-capable AI, this skill allows developers to upload screenshots or images and receive a deep-dive analysis of UI elements, layout structures, and textual content. It is a vital part of the Openclaw Skills library for teams needing to bridge the gap between visual bug reports and technical resolution.
Whether you are debugging a complex CSS layout issue or trying to extract text from a legacy system screenshot, this skill provides the context needed to understand the visual state of any application. It effectively automates the process of manual inspection by identifying buttons, menus, forms, and even subtle anomalies that might escape the human eye.
Screenshot Analyzer Use Cases
- Debugging UI/UX issues and layout inconsistencies in web or mobile applications.
- Extracting textual information and error messages from screenshots where text cannot be copied.
- Documenting software states and user flows for technical manuals or bug reports.
- Verifying that visual implementations match design specifications.
- Understanding unfamiliar interfaces or complex dashboards through automated description.
How Screenshot Analyzer Works
- The user uploads or provides a path to an image file (supporting PNG, JPG, GIF, or WebP).
- The skill processes the file using a vision-capable AI model to scan the visual layers.
- The AI identifies and categorizes UI elements, labels, icons, and text content.
- A structured report is generated, providing a comprehensive breakdown of the visual context and potential issues.
Screenshot Analyzer Setup
To integrate this capability into your workflow, ensure your environment is configured to use vision-enabled models. This skill is part of the standard Openclaw Skills distribution.
# Usage is triggered via natural language or direct command
analyze path/to/your/screenshot.png
Screenshot Analyzer Data Schema & Taxonomy
The skill generates a structured textual response based on the following metadata taxonomy:
| Section | Description |
|---|---|
| Overview | A high-level summary of what the image represents (e.g., a login page or a dashboard). |
| UI Breakdown | A list of identified interactive elements like buttons, navigation bars, and input fields. |
| Text Found | A full extraction of visible text and labels found within the image. |
| Analysis | Technical insights regarding layout issues, bugs, or anomalies. |
| Recommendations | Suggested fixes or next steps for the developer. |
Screenshot Analyzer Advanced Features
- Support for partial or cropped images to focus analysis on specific UI components.
- Contextual awareness that recognizes specific application states and user flows.
- Compatibility with multiple image formats including modern WebP and legacy formats.
- Integration ready for multi-agent workflows within the broader Openclaw Skills framework.
SKILL.md
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