A structured four-phase methodology for verifying UI behavior, visual consistency, and accessibility compliance.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install browser-qa
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install browser-qa using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Browser QA?
The Browser QA skill is a comprehensive testing framework designed for AI agents to perform rigorous quality assurance on web applications. By integrating this methodology into Openclaw Skills, developers can automate the detection of console errors, network failures, and performance bottlenecks before they reach production. The skill emphasizes a systematic approach to UI verification, ensuring that every user journey—from login to checkout—functions exactly as intended across various devices.
Beyond simple functional testing, this skill focuses on the visual and inclusive aspects of web development. It leverages visual regression techniques to catch layout shifts across multiple breakpoints and incorporates accessibility audits to ensure compliance with WCAG AA standards. This makes it an essential tool for teams looking to maintain high-quality frontend standards while leveraging the power of Openclaw Skills for automated testing.
Browser QA Use Cases
- Automating pre-shipment smoke tests to detect critical console errors and network request failures.
- Validating complex user interactions including form submissions, authentication flows, and navigation links.
- Performing multi-viewport visual regression testing to identify layout overflows on mobile and desktop.
- Conducting programmatic accessibility audits to ensure keyboard navigation and screen reader support meet industry standards via Openclaw Skills.
How Browser QA Works
- The agent performs a Smoke Test by navigating to the target URL to verify Core Web Vitals and check for 4xx/5xx network errors.
- It transitions to Interaction Testing, where it programmatically clicks links and submits forms with both valid and invalid data to verify state changes.
- Visual Regression is executed by capturing screenshots at 375px, 768px, and 1440px breakpoints to detect layout shifts or missing elements.
- An Accessibility Audit is conducted using axe-core to flag WCAG AA violations and verify the logical focus order for keyboard users.
- The process concludes with the generation of a detailed QA Report that provides a final verdict based on the severity of issues found.
Browser QA Setup
To utilize this skill within the Openclaw Skills ecosystem, ensure your agent has access to a browser automation environment such as Playwright or Puppeteer.
# Trigger a QA audit by providing the target URL to your agent
# Example command:
"Perform a full browser test on https://your-app-url.com"
No additional binary installations are required as the skill follows a methodology-based approach compatible with standard browser-capable AI agents.
Browser QA Data Schema & Taxonomy
The skill generates a structured QA Report following this metadata taxonomy:
| Section | Tracked Metrics |
|---|---|
| Smoke Test | Console errors, Network status codes, LCP, CLS, INP |
| Interactions | Link verification, Form success/error states, Auth flow status |
| Visual | Multi-breakpoint screenshots, Layout shift flags, Dark mode status |
| Accessibility | WCAG AA violations, Focus order validation, ARIA landmarks |
| Verdict | Final SHIP vs. FIX recommendation based on critical vs. warning count |
Browser QA Advanced Features
- Multi-breakpoint visual analysis for responsive design verification.
- Automated Core Web Vitals performance benchmarking (LCP, CLS, INP).
- Integrated axe-core accessibility scanning for automated WCAG compliance reporting.
- Detailed interaction logging to debug complex user journeys like multi-step checkout or onboarding within Openclaw Skills.
SKILL.md
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