An AI-powered skill for extracting, parsing, and analyzing text from terminal and command-line interface screenshots.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install terminal-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 terminal-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 Terminal OCR?
Terminal OCR is a specialized tool designed to bridge the gap between visual terminal outputs and actionable data. By utilizing advanced image preprocessing and multi-engine OCR capabilities, this skill allows AI agents to interpret CLI environments with high precision. It is a vital component of the Openclaw Skills ecosystem, enabling developers to process complex logs and command outputs directly from screenshots without manual typing.
The skill goes beyond simple character recognition by offering terminal-specific optimizations. It can reconstruct table structures, detect character encodings, and perform syntax highlighting for commands and paths. Whether you are troubleshooting remote server logs or explaining complex CLI outputs, Terminal OCR provides the technical accuracy required for professional development workflows.
Terminal OCR Use Cases
- Analyzing system logs from screenshots to diagnose server errors and identifying specific error codes.
- Parsing command-line tool outputs to provide step-by-step explanations or documentation.
- Extracting configuration settings from captured terminal views for rapid environment migration.
- Identifying timestamps and log levels within dense terminal data captures.
How Terminal OCR Works
- The user provides a screenshot of a terminal or command-line interface to the agent.
- The skill performs image preprocessing, including automatic chunking for long screenshots and contrast enhancement to improve readability.
- The system selects the best OCR engine—either Tesseract for local processing or AI vision models for complex visual analysis.
- Extracted text undergoes post-processing to restore table structures and identify CLI syntax like paths and commands.
- The final analyzed data is returned to the user with actionable insights or error diagnoses.
Terminal OCR Setup
To integrate this into your Openclaw Skills environment, follow these steps:
# Navigate to the skills directory
cd ~/.openclaw/workspace/skills/terminal-ocr
# Execute the installation script
bash install.sh
Ensure you have Python 3.8+, OpenCV, and Pillow installed. For optimal local performance, installing Tesseract OCR and its language packs is highly recommended.
Terminal OCR Data Schema & Taxonomy
The skill organizes its operations and outputs within a structured directory to ensure consistency across Openclaw Skills.
| File/Folder | Purpose |
|---|---|
/config/ocr-config.json |
Configuration for OCR engines and image processing parameters. |
/scripts/terminal-ocr.sh |
The primary entry point for processing terminal screenshots. |
/scripts/preprocess-image.py |
Python script handling binarization and contrast enhancement. |
/data/processed/ |
Internal storage for processed image segments and text results. |
package.json |
Defines the technical metadata and dependencies for the skill. |
Terminal OCR Advanced Features
- Hybrid Processing Mode: Combines local OCR engines with AI vision fallbacks to ensure high accuracy even in non-standard environments.
- Intelligent Image Chunking: Automatically splits ultra-long terminal screenshots into manageable segments for processing.
- Specialized Monospaced Optimization: Algorithms specifically tuned to recognize fixed-width fonts common in CLI environments.
- Automated Error Diagnosis: Dedicated scripts designed to specifically highlight and troubleshoot error patterns in log captures.
SKILL.md
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