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Skill939 repo starsupdated 3d ago

ss-verify

The VISUAL gate — render a UI or visual artifact through its surface adapter, inspect the actual pixels, then fix and re-render until it passes the composed StyleSeed rule set.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/bitjaru/styleseed /tmp/ss-verify && cp -r /tmp/ss-verify/skills/ss-verify ~/.claude/skills/ss-verify
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# Verify (look at it, don't just read it)
## Registry-first artifact boundary

When `.styleseed/project.json` and `.styleseed/artifacts/index.json` exist, resolve the requested artifact ID first, then read only `.styleseed/bundles/<artifact-id>.md` and `.styleseed/manifests/<artifact-id>.json`. Never fall back to the global legacy bundle for a registry project. Legacy projects may use `.styleseed/effective-rules.md` only when no registry exists.

Read `.styleseed/effective-rules.md` and `.styleseed/manifest.json`; invoke `/ss-resolve` or
`$ss-resolve` first when they are missing or stale. Judge pixels against that compiled method.
A lock value cannot excuse a core failure, and a recipe/profile cannot replace the output grammar.

`/ss-score` reads the **code** and scores it. But some of the worst "AI-made" tells never appear
in source — they only exist in **pixels**: a hero that doesn't actually dominate, a lower third
of dead whitespace, cramped cards, a web font that silently failed to load and fell back to
Times, two colors that *look* like two accents once rendered, text that's unreadable on its real
background. A human sees these in half a second; a code-reading gate misses all of them.

`/ss-verify` closes that gap: it **renders the UI, screenshots it, and you look at the image** —
then score the same StyleSeed gate against what you see, fix, and re-render. This is the gate
that most predicts whether a real user will say "this looks designed."

Run it as the **final** gate after `/ss-score` passes — code-clean is necessary but not
sufficient; pixel-clean is the real bar.

## When NOT to use

- Nothing renderable yet (pure logic/config, or a component with no host page) → use `/ss-score`.
- No way to render at all (no browser, no Playwright, headless blocked) → say so, fall back to
  `/ss-score`, and tell the user the visual gate was skipped. **Never claim you verified visually
  if you didn't actually see a screenshot.**
- A quick pre-commit pass → `/ss-lint`. `/ss-verify` is heavier (it boots a renderer).

## Step 1 — Render it through the active adapter

For `social-carousel`, `slide-deck`, `document-report`, or `single-frame`, use the companion
renderer and open every required exported frame/page at readable resolution. Verify dimensions,
crop/safe zones, font availability, asset placement, and the export manifest. Do not force a
browser workflow onto a PIL, slide, PDF, or image renderer.

For `product-ui`, get a real screenshot in priority order:

**A. Running project (Next / Vite / etc.) — the normal case.**
1. Start the dev server in the background (`npm run dev` / `pnpm dev` / framework command); wait
   for the ready line and capture the port.
2. Screenshot the route with headless Chromium via Playwright. If the project has `playwright`
   in `node_modules`, use it; else use a globally cached Chromium. Minimal script:
   ```js
   import { chromium } from "playwright";           // or an absolute path into node_modules
   const b = await chromium.launch();
   const c = await b.newContext({ viewport: SURFACE, deviceScaleFactor: 2 });
   const p = await c.newPage();
   await p.goto(URL, { waitUntil: "networkidle" });
   await p.evaluate(() => document.fonts.ready);      // don't shoot before fonts load
   await p.waitForTimeout(400);
   await p.screenshot({ path: OUT, fullPage: true });
   await b.close();
   ```
   **Surface viewports:** mobile `{width:390,height:844}` · desktop `{width:1440,height:900}`.
   Pick from the lock's `Surface`, or `--surface`.
3. If a browser MCP (claude-in-chrome) is available instead, navigate + screenshot with that.

**B. Static HTML file** → open it directly with `file://…` and screenshot (same script).

**C. Isolated component** (no host page) → render it into a minimal throwaway page that imports
the component with realistic props, then screenshot that.

**Then actually READ the screenshot back** (Read the PNG). You must *see* it. Shoot at
`deviceScaleFactor: 2` so text is crisp enough to judge.

## Step 2 — Score what you SEE (the visual gate)

Look at the image and run the StyleSeed gate **perceptually**. These are the checks that need
eyes, not source:

```
□ Squint test    — blur your focus / imagine it at 50%. Does it still read "AI-generated"?
                   (bland gradient, pill button + generic sans, icon-chip row, even flat grid) → FAIL
□ Focal          — does ONE element actually dominate at a glance? If your eye lands nowhere,
                   or on an all-even grid, the focal point failed regardless of what code intended
□ Balance        — dead whitespace (a lower third of empty), or cramped/colliding elements?
                   Is the visual weight distributed, or all top-left / all-centered?
□ Fonts loaded   — is the intended typeface actually rendering, or a Times/Arial fallback?
                   (a silent font-load fail is a top "looks cheap" tell — invisible in code)
□ One accent (seen) — count the hues you actually SEE. Two things competing for "the color" = FAIL,
                   even if the code named one token
□ Contrast (seen) — any text you have to strain to read on its real rendered background?
                   Light-grey-on-white labels, low-contrast on a colored/照片 panel
□ Rhythm/optics  — are edges aligned, gaps consistent, cards optically even? Off-by-a-few-px
                   misalignments that read as "sloppy" but pass a code check
□ Type scale fit — on desktop, does the body text look too small for the canvas? does the hero
                   feel undersized? (the surface-scale tell, judged by eye)
□ Grammar fit   — does the screen visually serve the selected grammar's user job, attention
                   model, composition, density, action hierarchy, and characteristic tells?
□ Recipe fit    — do geometry, containment, controls, collections, navigation, density, and
                   motion visibly match the selected recipe rather than the old universal soft-card look?
                   Woul