A high-precision OCR utility that transforms screenshots and clipboard images into editable text, supporting multiple languages and formats.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install screenshot-ocr
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-ocr 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 OCR?
Screenshot OCR is a versatile technical tool designed for the Openclaw Skills ecosystem. It bridge the gap between static visual data and actionable text by utilizing the Tesseract engine to recognize characters in screenshots or images stored in the clipboard. Whether you are dealing with complex tables, verification codes, or documentation snippets, this skill ensures rapid extraction with minimal friction.
By integrating this Openclaw Skills asset into your workflow, you can bypass manual typing and move directly from capturing an image to utilizing its content. It is particularly effective for developers and researchers who need to pull text from legacy interfaces or video frames where standard text selection is unavailable.
Screenshot OCR Use Cases
- Extracting code snippets or error messages from tutorial videos or locked web pages.
- Converting tabular data found in images into structured text formats for data entry.
- Capturing and digitizing text from system notifications or verification codes.
- Automating the translation of visual content by first converting it to plain text.
How Screenshot OCR Works
- The user captures a screenshot to the system clipboard or specifies a local image file path.
- The Openclaw Skills command-line interface triggers the OCR script, which utilizes the Pillow library for image processing.
- The Pytesseract engine analyzes the image data to identify characters in Chinese, English, or numerical formats.
- The identified text is processed and either printed to the console, copied to the clipboard, or written to a designated file based on the user's flags.
Screenshot OCR Setup
First, ensure you have the Tesseract engine installed on your system:
# Linux
sudo apt install tesseract-ocr tesseract-ocr-chi-sim
# macOS
brew install tesseract
# Windows
# Download and install from: https://github.com/UB-Mannheim/tesseract/wiki
Then, install the necessary Python dependencies for this Openclaw Skills module:
pip install pytesseract pillow
Screenshot OCR Data Schema & Taxonomy
The skill processes image inputs and produces text outputs. Data management is handled via the following parameters:
| Input Type | Argument | Output Option |
|---|---|---|
| System Clipboard | clipboard |
Console Output |
| Image File | file [path] |
--save [filename.txt] |
| Processed Text | N/A | --copy (to Clipboard) |
Files generated by the --save command are standard UTF-8 encoded text files.
Screenshot OCR Advanced Features
- Support for table recognition to maintain structural integrity of data during extraction.
- Multi-language support including Simplified Chinese and English (Tesseract-based).
- Direct clipboard-to-clipboard workflow for maximum speed in Openclaw Skills environments.
- Automated file saving with custom naming conventions for batch processing logs.
SKILL.md
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