What problem does it solve? Code and spec audits can pass while the rendered UI is still visually wrong — asymmetric padding, hover backgrounds eating declared gaps, misaligned baselines, broken overlay positioning, or dark-mode token mismatches. This Skill catches those pixel-level defects by mechanically measuring screenshots against design-system tokens and specs. ## Core Features & Use Cases - 13-item mechanical checklist: Measures 4-side padding symmetry, vertical symmetry, gap token fidelity, overlay positioning, typography baseline alignment, icon-text gaps, container fill, field height alignment, scrollbar consistency, zoom step ratio, dark-mode token behavior, overflow indicator occlusion, and arrow button placement. - Two-layer architecture: Consumes Layer A mechanical evidence (Playwright screenshots, WCAG contrast scans, geometry assertions from npm run visual-audit) and applies Layer B AI judgment for design reasonableness and world-class benchmark comparison. - Strictly read-only reporting: Produces a structured Markdown audit report with PASS/FAIL/undetermined verdicts, measured vs expected values, and routed remediation — never edits code, specs, or stories. - Use Case: A user uploads a Storybook screenshot of a DatePicker asking whether the layout is correct; the Skill measures that bottom padding is 8px versus the 12px spec token and files a FAIL with the exact delta and governing rule. ## Quick Start Upload a Storybook screenshot of a component and ask the assistant to run a visual audit on it against the design-system spec.