A high-performance image processing skill utilizing libvips for memory-efficient resizing, format conversion, and batch operations.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install libvips-image
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 libvips-image 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 libvips Image Processing Skill?
The libvips image processing skill is a professional-grade tool designed for high-performance media manipulation. By integrating this into your Openclaw Skills library, you gain access to a streaming architecture that processes images in small chunks, ensuring that memory usage remains low even when handling massive files. It is significantly more efficient than traditional libraries like ImageMagick or PIL, often using 10 to 100 times less memory during heavy operations.
Whether you are building a web optimization pipeline or automating asset management, this entry in the Openclaw Skills registry provides the speed and reliability required for production environments. It supports over 300 operations, including smart cropping, rotation, and multi-format conversion, making it a versatile choice for any developer looking to scale their image processing workflows.
libvips Image Processing Skill Use Cases
- Efficiently resize, crop, or create thumbnails for large image libraries
- Convert between modern web formats including JPEG, PNG, WebP, AVIF, and HEIC
- Automate the application of watermarks or text overlays for branding
- Batch process entire directories of images for web optimization or archival
- Handle extremely large images (like TIFF or PDF) with minimal system memory usage
How libvips Image Processing Skill Works
- The user installs the libvips system library and the pyvips Python wrapper using the automated installation scripts.
- The skill identifies the target image file or input directory based on the provided CLI arguments.
- A processing pipeline is constructed using operations such as resize, convert, or sharpen.
- libvips executes the pipeline using a streaming, sequential access model to minimize the memory footprint.
- The finalized image is written to the output destination with specified quality and compression settings.
libvips Image Processing Skill Setup
To get started with this skill in your Openclaw Skills environment, use the recommended auto-detection script:
# Recommended: Auto-detect OS and install dependencies
./scripts/install.sh
For manual installation on macOS via Homebrew:
brew install vips
uv pip install pyvips
For Ubuntu/Debian users:
sudo apt-get install libvips-dev
uv pip install pyvips
libvips Image Processing Skill Data Schema & Taxonomy
The skill processes various image formats and accepts specific parameters via CLI or JSON configuration. Below is a breakdown of supported formats:
| Format | Read | Write | Notes |
|---|---|---|---|
| JPEG | Yes | Yes | Quality 1-100 |
| WebP | Yes | Yes | Lossy and lossless support |
| AVIF | Yes | Yes | High compression efficiency |
| PNG | Yes | Yes | Compression levels 0-9 |
| HEIC | Yes | Yes | Apple standard format |
Primary CLI Parameters:
--width/--height: Target pixel dimensions--quality: Output quality (default 85)--mode: Resize behavior (fit, cover, force)--crop: Smart cropping strategies (attention, centre, entropy)--sigma: Radius for blur or sharpen filters
libvips Image Processing Skill Advanced Features
- Smart cropping using attention-based algorithms to focus on interesting image areas
- Asynchronous batch processing with configurable worker threads and JSON-based configurations
- Sequential access streaming to process multi-gigabyte images without crashing system memory
- Chained operation pipelines that allow multiple transformations in a single execution pass
- Support for advanced blending modes and composite overlays for complex watermarking
SKILL.md
Loading
Related Openclaw Skills
Gemini Watermark Remover
An offline Python tool that uses reverse alpha blending to mathematically remove the star logo from Gemini-generated images.
Garmin Health Report
A powerful Python-based tool for generating comprehensive daily health and professional running reports from Garmin Connect data.
WhaleWatch
WhaleWatch is a sophisticated blockchain monitoring tool that tracks large-scale wallet movements and identifies high-performance smart money traders.
TokenSniper
A powerful real-time monitoring and risk assessment tool for identifying and analyzing new cryptocurrency launches across multiple chains.
Qwen3-TTS MLX
A high-performance local text-to-speech engine optimized for Apple Silicon that supports voice cloning and natural language voice design.
Autonomous Bookkeeper
A sophisticated meta-skill that automates the pre-accounting lifecycle by orchestrating email intake, OCR data extraction, payment verification, and accounting record creation.
Featured*
