CLI-QR-Refiner is a professional utility designed to convert raw ASCII and Unicode terminal character blocks into crisp, high-definition PNG images.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install cli-qr-refiner
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 cli-qr-refiner 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 CLI-QR-Refiner?
CLI-QR-Refiner provides a robust solution for developers and AI agents working in headless or terminal-heavy environments where QR codes are often rendered using block characters like █, ▀, and ▄. These characters frequently fail to scan due to terminal font issues, line-height inconsistencies, or alignment problems. As a specialized addition to Openclaw Skills, this tool ensures zero scanning failures by providing vector-like precision during the conversion process.
By leveraging Python and the Pillow library, CLI-QR-Refiner acts as a bridge between low-fidelity CLI outputs and high-fidelity mobile scanning applications. It is particularly valuable for Openclaw Skills users who need to handle authentication flows (such as WeChat or Aliyun) or package registry logins directly from their automation workflows.
CLI-QR-Refiner Use Cases
- Refining ASCII QR code blocks generated by CLI tools like WeChat, Aliyun, or NPM for reliable mobile scanning.
- Troubleshooting scanning failures caused by terminal-specific font distortion or line-spacing issues.
- Automated extraction and delivery of QR codes from remote server logs to end-users as high-quality image files.
- Converting Unicode-based matrices into PNG format for documentation or historical logging.
How CLI-QR-Refiner Works
- The tool parses the input text file to recognize specific Unicode block characters (█, ▀, ▄) and whitespace.
- It maps each character to a corresponding pixel cell: full black for █, upper-half for ▀, lower-half for ▄, and white for spaces.
- The script applies pixel-perfect scaling based on the user-defined scale parameter (defaulting to 10).
- A final high-definition PNG image is rendered and saved to the specified output path.
CLI-QR-Refiner Setup
To utilize this within your Openclaw Skills environment, ensure you have Python 3 and the Pillow library installed. No other external dependencies are required.
# Install Pillow if not already present
pip install Pillow
# Basic usage command
python3 scripts/cli_qr_refiner.py <input_txt_path> <output_png_path> [scale]
CLI-QR-Refiner Data Schema & Taxonomy
| Component | Description |
|---|---|
| Input Format | Raw .txt file containing ASCII/Unicode block characters (UTF-8 encoding recommended). |
| Output Format | Standard .png image file with high contrast for scanning optimization. |
| Character Mapping | █ = 100% Black; ▀ = Top 50% Black; ▄ = Bottom 50% Black; Space = 100% White. |
| Metadata | Part of the openclaw metadata namespace requiring the python3 binary. |
CLI-QR-Refiner Advanced Features
- Pixel-Perfect Scaling: Support for custom scale parameters to ensure images remain crisp at any resolution.
- Headless Optimization: Designed specifically for server-side execution where no display environment is available.
- Multi-Block Interpretation: Advanced recognition of partial block characters (upper/lower half) to support compact terminal QR rendering styles.
- Openclaw Agent Integration: Pre-configured prompting behavior for AI agents to automatically handle QR capture-save-refine-deliver loops.
SKILL.md
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