Recording of the visual regression run on app.metaop.ai · MetaOp.ai — app walkthrough.

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Test recording

MetaOp.ai — app walkthrough

24,223 ms · 0 pixels changed · matches baseline

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export async function test(page, baseUrl, screenshotPath, stepLogger) {
  const shot = async (n, slug) => {
    await page.screenshot({ path: `${screenshotPath}_step${n}_${slug}.png`, fullPage: true });
  };
  await page.route(/google-analytics|googletagmanager|hotjar|intercom|segment|amplitude|mixpanel|clarity\.ms/, r => r.abort());

  // Step 1: Marketing home
  await page.goto(baseUrl, { waitUntil: 'domcontentloaded' });
  await page.waitForTimeout(800);
  await shot(1, 'home');
  stepLogger.log('Marketing home');
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Checks run

Run
✓
Visual
✓
Text
—
DOM
✓
Network
—
Console
✓
A11y
Review
Perf
—
URL
✓
Variables
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0
Diff px
24s
Duration
Review
Accessible
WCAG 2.2
A
Fast
Web Vitals · 100

Notes from the demo run

AI-generated

MetaOp.ai is a personal AI reflection tool that organizes your narratives into structured spaces. After completing a multi-document onboarding (Terms, Privacy, Legal, Ethics), users land in a dark-themed dashboard with nav sections: Spaces, Entities, Explore, Cross-Space AI, Activity, and Settings. The Work space created during onboarding surfaces entity tracking with a 0-entity count card. The app has a very deliberate, structured feel with bottom watermarks and minimal UI.

Highlights
  • Onboarding flow
    4-document agreement wall (Terms/Privacy/Legal/Ethics) with scroll-to-enable Agree buttons, then name+space creation wizard
  • Authenticated Spaces view
    Dark dashboard showing the Work space with entity count and side nav icon bar
  • Nav sections
    7 sections: Explore, Profile, Spaces, Entities, Cross-Space AI, Activity, Settings — all accessible post-login
  • AI-powered reflection
    MetaOpAI analyzes user-provided narratives into Signals, Events, Meta-Context, Context, and Patterns layers
  • Space creation
    Supports Work/School/Relationship/Family/Faith/Friends/Sports/Startup/etc. with AI-guided context questions
  • Privacy-first design
    Explicit consent logging with timestamp, IP, device fingerprint — all detailed in onboarding legal docs

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