/SKILL.md
A production-grade, Rust-powered image optimization engine for AI Agents. Smartly routes between PNG quantization and WebP compression.
npx skillsauth add 994ak/image-compress-skill image-compress-skillInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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The intelligent image optimization engine for AI Agents. Smart routing between PNG quantization and WebP compression.
The optimal compression strategy depends on the input content type and the target use case.
| Content Type | Primary Strategy | Toolchain | Target Format |
| :--- | :--- | :--- | :--- |
| Photographs | Lossy WebP | image -> libwebp | .webp |
| Graphics / Logos / UI | Optimized PNG | image -> imagequant -> oxipng | .png |
| Universal (Web) | WebP (High Compat) | image -> libwebp | .webp |
| Universal (Archive) | Optimized PNG | image -> oxipng (Lossless) | .png |
Decision Logic:
oxipng (PNG) or Lossless WebP.This skill requires the image-compress-tool binary.
If the tool is not found, the agent should run:
./scripts/install.sh
Best for: Photos, complex gradients, web assets.
-q):
-m):
// Rust (using webp crate)
let encoder = webp::Encoder::from_image(&img)?;
let memory = encoder.encode(80.0); // Q=80
imagequant + oxipng)Best for: Logos, icons, screenshots, line art, transparent assets.
imagequant)
min=0, max=80 (or 80-90 for high fidelity).4 (Default). 1 (Slowest/Best).oxipng)
-o):
--strip safe): Remove metadata.-i 0): Disable interlacing (saves ~20%).// Pipeline
let (palette, pixels) = imagequant_attributes.quantize(img)?; // Step 1
let png_data = encode_png(palette, pixels);
let optimized = oxipng::optimize_from_memory(&png_data, &options)?; // Step 2
When implementing image compression tools:
[dependencies]
image = "0.25"
imagequant = "4.4"
oxipng = "10.1"
webp = "0.3"
anyhow = "1.0"
clap = { version = "4.5", features = ["derive"] }
See image-compress-tool/src/main.rs in the current project for the reference implementation that handles:
webp crate)imagequant -> png encoding -> oxipng)Always verify:
development
Maintainer-only workflow for handling GitHub Secret Scanning alerts on OpenClaw. Use when Codex needs to triage, redact, clean up, and resolve secret leakage found in issue comments, issue bodies, PR comments, or other GitHub content.
development
Maintainer workflow for OpenClaw releases, prereleases, changelog release notes, and publish validation. Use when Codex needs to prepare or verify stable or beta release steps, align version naming, assemble release notes, check release auth requirements, or validate publish-time commands and artifacts.
development
Run, watch, debug, and extend OpenClaw QA testing with qa-lab and qa-channel. Use when Codex needs to execute the repo-backed QA suite, inspect live QA artifacts, debug failing scenarios, add new QA scenarios, or explain the OpenClaw QA workflow. Prefer the live OpenAI lane with regular openai/gpt-5.4 in fast mode; do not use gpt-5.4-pro or gpt-5.4-mini unless the user explicitly overrides that policy.
development
End-to-end Parallels smoke, upgrade, and rerun workflow for OpenClaw across macOS, Windows, and Linux guests. Use when Codex needs to run, rerun, debug, or interpret VM-based install, onboarding, gateway smoke tests, latest-release-to-main upgrade checks, fresh snapshot retests, or optional Discord roundtrip verification under Parallels.