Recording of the visual regression run on app.tagzzs.com · Tagzzs — app walkthrough.

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Tagzzs — app walkthrough

82,023 ms · 137,954 pixels changed

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export async function test(page, baseUrl, screenshotPath, stepLogger) {
  const shot=(n,s)=>screenshotPath.replace('.png','-'+n+'-'+(String(s).replace(/[^a-z0-9]+/gi,'-').replace(/^-|-$/g,'').toLowerCase().slice(0,22)||'view')+'.png');
  const ORIGIN="https://app.tagzzs.com"; const MINPOST=9;
  await page.context().setExtraHTTPHeaders({ 'User-Agent': "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Safari/537.36" }).catch(function(){});
  let idx=1, post=0;
  const cap=async(s,full)=>{ stepLogger.log('Scenario '+idx+': '+s); await page.screenshot({ path: shot(idx,s), fullPage: full!==false }); idx++; };
  const accept=async()=>{ await page.getByRole('button',{name:/accept all|got it|^accept$|dismiss|^close$|skip|maybe later|not now|^ok$/i}).first().click({timeout:1200}).catch(function(){}); await page.keyboard.press('Escape').catch(function(){}); };
  // 1. Public home
  await page.goto("https://tagzzs.com",{waitUntil:'domcontentloaded'}).catch(function(){}); await page.waitForLoadState('networkidle',{timeout:6000}).catch(function(){}); await page.waitForTimeout(1500); await accept(); await cap('home');
  // 2. Dashboard (authed)
  await page.goto(ORIGIN+'/dashboard',{waitUntil:'domcontentloaded'}).catch(function(){}); await page.waitForLoadState('networkidle',{timeout:9000}).catch(function(){}); await page.waitForTimeout(4500); await accept(); await page.waitForTimeout(800); await cap('dashboard-consumption'); post++;
  // 3. Business interaction: ADD CONTENT (the second-brain capture flow)
+33 more lines claim the test to get the full code.

Checks run

Run
Visual
10.50%
Text
DOM
Network
+22 −517
Console
A11y
C
Perf
33 over
URL
11 diverged
Variables
Full report
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137,954
Diff px
1m 22s
Duration
C
Accessible
WCAG 2.2 · 76
B
Fast
Web Vitals · 85

Notes from the demo run

AI-generated

Tagzzs positions itself as a 'second brain for the internet age' - paste a YouTube video, article, X thread, Instagram reel or PDF URL and it tags and files the content into structured 'stacks' you can later query with an AI assistant (Kai). Onboarding asks which topics you care about and pre-loads a starter library, so the dashboard shows real saved content on first login rather than an empty state. The authed shell is focused: a consumption dashboard, a Knowledge Base of stacks, the Kai AI assistant, and Settings.

Highlights
  • Topic-seeded first run
    Onboarding ('pick the topics you care about') pre-loads a starter stack, so the dashboard immediately shows saved items, a stack distribution and recent activity - no cold empty state.
  • Format-agnostic capture
    The 'Add Content' dialog accepts YouTube, articles, X threads, Instagram reels, Substack and PDF-via-URL from a single paste field - the capture surface is genuinely broad.
  • AI over your own library (Kai)
    Kai is scoped to ask questions across your saved content, not just general chat - the differentiator over a plain bookmarking tool.
Friction points
  • Credit cost surfaced at capture
    The Add-Content action shows a '50 credits' debit up-front; clear, but it makes a first-time user hesitate before saving their first link on the Basic plan.
  • Lean top-level nav
    Dashboard / Knowledge Base / Kai / Settings is tidy but discovery of stacks and filters relies on in-page controls rather than the sidebar.

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