Compresses and resizes images to standardize dimensions and quality.
npx skills add https://github.com/FassadenFix/FaFi --skill image-optimizer-fassadenfix
Please help me install this Agent Skill. Skill: image-optimizer Source: https://github.com/FassadenFix/FaFi/tree/main/skills/image_optimizer Command: npx skills add https://github.com/FassadenFix/FaFi --skill image-optimizer-fassadenfix
This Skill eliminates manual image optimization by automatically compressing and resizing images to standard dimensions and quality, improving load times and storage efficiency.
Run the optimizer on an image by providing the path to the image file. Example: python3 main.py '{"image_path":"/path/to/image.jpg"}'
High-intent search queries and answers about installing and using this skill.
To compress and resize images for web assets automatically, you run a Python script that reads local image paths and writes optimized files with a _optimized suffix. This process reduces file size while preserving visual quality and maintaining aspect ratio.
The best way to optimize product photos for an online store is to use an automated workflow that scales images to a standard maximum dimension, such as 1024px. This ensures consistent dimensions and quality across your entire product catalog.
You can optimize images in a local media library by applying a deterministic Python workflow to your local image paths. This automates the compression and resizing tasks to ensure consistent dimensions and improved storage efficiency.
No external libraries are required to run this image optimization workflow. It operates using a deterministic Python script with no dependencies, reading local image files directly and outputting the optimized versions.
Image compression reduces file size while preserving the visual quality of web assets. The workflow applies smart resizing that keeps the aspect ratio intact, ensuring images remain clear and consistent for website page loads.
To start resizing a local image using Python, you execute the main script and pass a JSON string containing the local image_path. The workflow reads this input and writes the resized, compressed output file with an _optimized suffix.
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