Performance Smoke Test

Enter key web performance metrics and get a pass/warn/fail release report scored against page-type budgets.

Runs 100% client-side
Copy outputCSV & Markdown export
On this page4 sections

Metrics (leave blank to skip)

Largest Contentful Paint — when the main content becomes visible.

Cumulative Layout Shift — how much the layout jumps as it loads.

Interaction to Next Paint — responsiveness to user input.

Time To First Byte — server/network response latency.

Total transferred bytes for the page.

Transferred JavaScript bytes — a common interactivity bottleneck.

Number of network requests made by the page.

HOW TO USE

  1. 01Pick the threshold preset that matches the page (login, checkout, dashboard, and so on).
  2. 02Enter the metrics you have — LCP, CLS, INP, TTFB, page size, JS size, requests. Leave the rest blank.
  3. 03Click Evaluate to score each metric pass / warn / fail against the budget.
  4. 04Copy or download the release report to share the overall result and biggest risks.

Try it

Preset = Checkout, LCP = 3.4, CLS = 0.04, TTFB = 1200 → see LCP and TTFB flagged as warnings.

WHEN TO USE

Use this when you can't run a full performance test before every release but still need to catch obvious regressions. Read the Core Web Vitals from Lighthouse, DevTools, or field data, drop them in, and get a quick pass/warn/fail verdict scored against budgets tuned for the page type. It is a smoke check, not a substitute for proper load and performance testing.

WHAT BUGS THIS FINDS

  • Slow main content (LCP) regressions

    An oversized hero image or render-blocking resource pushes LCP past 2.5s — scored as a warning or fail before users feel it.

  • Layout instability (CLS)

    Late-loading images or ads shift content and frustrate users — flagged against the 0.1 budget.

  • Page-weight creep

    Total page size and JavaScript budgets catch bundles and assets that have grown release over release.

QA USE CASES

01

Pre-release smoke check

Score a key page's vitals against its budget and decide whether performance is good enough to ship.

02

Mobile vs desktop comparison

Run the same metrics for each device profile to spot mobile-only regressions.

03

Performance bug evidence

Attach the generated report to a ticket so the numbers and budget are explicit.