Recording of the visual regression run on www.askcurator.io · AskCurator — app walkthrough.

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Test recording

AskCurator — app walkthrough

49,076 ms · 0 pixels changed · matches baseline

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export async function test(page, baseUrl, screenshotPath, stepLogger) {
  await page.route('**/(hotjar|analytics|amplitude|segment|posthog|intercom|crisp).**', route => route.abort());
  await page.route('**/collect?**', route => route.abort());

  stepLogger.log('AskCurator homepage');
  await page.goto('https://www.askcurator.io', { waitUntil: 'domcontentloaded' });
  await page.waitForTimeout(2500);
  await page.screenshot({ path: screenshotPath });

  stepLogger.log('App workbench');
  await page.goto('https://www.askcurator.io/app', { waitUntil: 'domcontentloaded' });
  await page.waitForTimeout(3000);
+46 more lines — claim the test to get the full code.

Checks run

Run
✓
Visual
✓
Text
—
DOM
✓
Network
+1089 −0
Console
✓
A11y
C
Perf
—
URL
✓
Variables
—
Full report
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0
Diff px
49s
Duration
C
Accessible
WCAG 2.2 · 70
A
Fast
Web Vitals · 100

Notes from the demo run

AI-generated

AskCurator is an AI-powered data analysis workbench where users upload datasets and ask natural language questions to get instant SQL-backed insights. The app is clean and developer-friendly with a spreadsheet-style data table and chat-style query interface side by side.

Highlights
  • Instant data import
    One click loads the Titanic sample dataset into a live, paginated table — no upload friction.
  • Natural language queries
    Ask in plain English (e.g. "What is the average age of survivors?") and get a generated SQL query + result instantly.
  • Workflow automation
    Workflows page lets you chain queries into repeatable pipelines — strong recurring-analysis use case.
  • Clean authenticated UX
    Post-login surface is minimal and focused: data on the left, query chat on the right, no onboarding clutter.

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