In the Skill's Own Terms
Designer's-eye QA of a live site. It opens pages in the user's own browser, screenshots them at 375, 768 and 1440, grades ten categories from visual hierarchy to interaction states, then edits source to fix what it found, one commit per fix, re-verifying with before and after screenshots.
Depth defaults to 5-8 pages; with no URL on a feature branch it goes diff-aware. Readers get two headline grades, a weighted Design Score and a standalone AI Slop Score, plus 30 named detector rules such as [kicker-above-heading] and [gradient-text] behind the judgment calls.
What it produces
- A structured markdown audit report in the run directory.
- A design-baseline.json file written for regression comparison on later runs.
- Before and after screenshot pairs for every applied fix.
- An optional DESIGN.md written from the extracted observations, if the user accepts the Phase 2 offer.
How It Works
- 01React Before You Analyze
Phase 1 opens the target and takes a full-page desktop screenshot, then writes a structured first impression naming what the eye goes to first.
- 02Extract the Rendered System
Phase 2 probes fonts, colors, heading scale and touch targets inside the page, then offers to save the findings as a DESIGN.md.
- 03Audit Page by Page
Phase 3 runs a console hook, interactive snapshot and annotated screenshot per page, then repeats at three viewport widths.
- 04Feel the Flows
Phase 4 walks 2-3 user flows, diffing the snapshot after each action and tracking a goodwill score for friction and repair.
- 05Fix One Finding at a Time
Phase 8 makes the minimal change, commits it alone, and re-tests before moving to the next finding.
- 06Score Two Headlines
The design score is a weighted average across ten categories, while the AI slop grade stands on its own.