ego-webqa

Deterministic coarse delivery QA for AI-generated web pages, H5 demos, and PWAs.

Point it at a URL. It opens the page in a real Chromium browser by default, checks a zero-config narrow-mobile matrix, safely probes the primary call to action, and leaves screenshots plus machine-readable evidence behind. Firefox and Playwright WebKit can be selected one engine at a time. The default eight variants combine:

• 360px and 390px widths;
• 1.0x and 1.5x text scaling;
• 0px and 34px simulated bottom safe area.

See the result in 30 seconds

Prefer to inspect a completed run first? Open the live before-and-after evidence board.

python -m pip install ego-webqa
ego-webqa setup
ego-webqa https://your-preview.example --out .qa/first

setup first checks the selected browser. If it already launches, setup exits without downloading anything; otherwise it installs the pinned Playwright headless shell with the active ego-webqa Python interpreter and verifies a real headless launch. The first Chromium setup avoids the full headed browser build because audits only run headless. Ordinary doctor and audit commands never download a browser implicitly. The audit command exits 0 for pass/warnings, 1 for blocking delivery defects, and 2 for an audit or browser failure. Each run leaves screenshots and structured evidence:

.qa/first/
├── agent_summary.json   # one aggregated, repair-ready item per root cause
├── feedback_bundle.json # privacy-safe summary for external issue reports
├── report.json
├── junit.xml
├── report.sarif
└── screenshots/

A real dogfood finding looks like this:

{
  "dimension_id": "text_scale_layout_break",
  "selector": "body > div:nth-of-type(2) > div:nth-of-type(2) > a",
  "text_snippet": "我也要创建 →",
  "problem": "page is 9px wider than the viewport at 1.5x text scale",
  "trigger": "mobile-360-150-safe0 (360x800); mobile-360-150-safe34 (360x800)",
  "severity": "block"
}

The report explains what broke, where it happened, which viewport combinations were affected, and gives the Agent a command that reproduces the failure.

What real pages exposed

The v0.8.2 dogfood pass audited all 20 Ego-owned production or canonical generated pages with zero runtime errors. After separating network-sensitive performance observations from deterministic delivery findings, ten pages were clean and ten had actionable structural findings. Stable failures included six text-enlargement layout breaks, four bottom safe-area penetrations, five clipped-text root causes, four undersized-target groups, and one generated page loading a missing service worker. There are no known stable blocking false positives in this corpus. This is a small, disclosed corpus rather than a market-wide accuracy claim; the full evidence, raw mixed-profile counts, and limitations are in docs/real-world-dogfood-2026-10-31-v0.8.2.md.

Layout failures now identify the deepest

... View full README on GitHub