Stop letting your coding agent claim "pixel-perfect". Make it prove 97.49%.

Your coding agent edits a component, runs the build, and reports the UI is now "pixel-perfect." It never opened a browser. It's guessing. I got tired of that, so I built hwatu, a browser designed specifically for the agent verification loop.

The loop:

hwatu --headless http://localhost:3000 # open, no focus steal
hwatu wait-load                        # block until loaded
hwatu eval 'document.title'            # DOM-level checks
hwatu shot /tmp/check.png              # screenshot
hwatu diff --id 1 --baseline before.png # pixel diff: 97.49% match + heatmap
hwatu close 1

The whole loop, screenshot included, runs in about 87 ms on my laptop. Cheap enough that the agent can verify after every edit instead of claiming success blind.

Design choices

• Headless by default in agent environments. Windows never steal focus while you keep typing. When you want to look, the agent hands you the same live window as a normal browser.
• No Chromium. One static Rust binary plus your distro's webkitgtk-6.0. No 170 MB download per project.
• Three protocols. MCP (hwatu mcp), plain CLI, and a 1-line JSON socket. Works with Claude Code, Cursor, Jcode, or any harness.
• Real numbers. The diff command reports an actual match percentage with a heatmap, so "pixel-perfect" becomes a measurable claim.

Measured, not estimated

Every benchmark in the repo was measured on real runs with scripts you can rerun: window spawn medians of 13-16 ms, ~87 ms full verification loop, memory measured via PSS across all WebKit child processes. Methodology in docs/benchmarks.md.

Try it

curl -fsSL https://raw.githubusercontent.com/hongnoul/hwatu/main/scripts/install.sh | bash
hwatu setup   # detects Claude Code, Cursor, Jcode, or generic MCP

MIT licensed. Linux (WebKitGTK). Feedback and issues welcome: https://github.com/hongnoul/hwatu

Forcing the agent to produce a number instead of an adjective is the right instinct - it is the same reason we make models report confidence against a held-out set instead of saying "looks good". One caveat from doing visual diffs: a single global similarity score hides where the error is. 97.49% can mean a uniform antialiasing difference nobody would notice, or a button in the wrong place with everything else identical. Region-weighted scores, or at least reporting the worst tile rather than the mean, makes the metric much harder to game.