Sharp Image Pipeline Processor
Builds composable image transformation pipelines using the Sharp library with operations like resize(), composite(), and toFormat(). Leverages libvips bindings for high-performance batch processing.
npx skills add agentskillexchange/skills --skill sharp-image-pipeline-processor-2
The Sharp Image Pipeline Processor creates composable image transformation workflows using the Sharp library’s fluent API backed by libvips native bindings. It chains operations like sharp(input).resize({ width, height, fit: “cover” }).composite([{ input: watermark, gravity: “southeast” }]).toFormat(“webp”, { quality: 80 }) for efficient multi-step processing.
What this skill actually does
Core capabilities include intelligent resizing with sharp.fit options (cover, contain, fill, inside, outside), metadata-aware orientation correction via rotate() with EXIF auto-rotation, and color space manipulation through toColorspace() for print-ready CMYK output. The processor handles batch operations using sharp.concurrency() tuning for optimal CPU utilization.
Advanced features include SVG overlay compositing with blend modes, animated GIF/WebP processing through the pages option for frame manipulation, and tile generation via .tile({ size: 256 }) for deep-zoom image viewers. It supports ICC profile embedding through withMetadata({ icc }) and provides streaming pipelines via sharp().pipe() for memory-efficient processing of large images without buffering entire files.