What problem does it solve? Color bugs in interfaces are usually system bugs: values picked in isolation, tokens borrowed because they looked right, and contrast pairs nobody measured. This Skill provides a rigorous methodology for building and auditing color systems so every value has a role, every token has a consistent name, and every contrast claim is measured rather than estimated. ## Core Features & Use Cases - Palette Generation: Build perceptually uniform color ramps from a brand color using libraries like culori, with even lightness steps, constant hue, and correct light-end density. - Token Architecture: Establish a two-tier primitive/semantic token system with a consistent naming grammar (--color-{role}-{variant}-{state}) that makes dark mode and theming possible. - Contrast Measurement: Measure foreground/background pairs against APCA (Lc) or WCAG 2 thresholds and report failures without silently repainting design decisions. - Use Case: When auditing a codebase, inventory every color literal, collapse near-duplicates, assign each survivor a role, and produce a severity-ranked findings table grouped by violated principle. ## Quick Start Ask the AI to audit the color tokens in your stylesheet and report any contrast failures, naming inconsistencies, or ramp problems it finds.