Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
日本語の概要は準備中です。原文の説明を表示しています。
Advanced visual regression testing with pixel-perfect comparison, AI-powered diff analysis, responsive design validation, and cross-browser visual consistency. Use when detecting UI regressions, validating designs, or ensuring visual consistency.
日本語の概要は準備中です。原文の説明を表示しています。
実行スコア 未検証
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
<default_to_action> When detecting visual regressions or validating UI:
Quick Visual Testing Steps:
Critical Success Factors:
| Bug Type | Description |
|---|---|
| Layout shift | Elements moved position |
| Color change | Unintended color modification |
| Font rendering | Typography issues |
| Alignment | Spacing/alignment problems |
| Missing images | Broken image paths |
| Overflow | Content clipping |
| Algorithm | Best For |
|---|---|
| Pixel diff | Exact match requirement |
| Structural similarity | Handle anti-aliasing |
| AI semantic | Ignore insignificant changes |
Most visual regression work should go through the qe-browser fleet skill. It wraps Vibium (WebDriver BiDi) and provides pixel-diff against stored baselines with threshold enforcement and diff-image output. See .claude/skills/qe-browser/SKILL.md.
# Navigate
vibium go https://example.com
vibium wait load
# First run — creates baseline in .aqe/visual-baselines/homepage.png
node .claude/skills/qe-browser/scripts/visual-diff.js --name homepage
# Subsequent runs — compare, non-zero exit on mismatch
node .claude/skills/qe-browser/scripts/visual-diff.js --name homepage --threshold 0.02
# Scope to a single region
node .claude/skills/qe-browser/scripts/visual-diff.js --name hero --selector "#hero"
# Responsive — run diff at each breakpoint
for viewport in "375 667" "768 1024" "1920 1080"; do
read w h <<< "$viewport"
vibium viewport $w $h
node .claude/skills/qe-browser/scripts/visual-diff.js --name "homepage-${w}x${h}"
done
# Reset baseline after an intentional design change
node .claude/skills/qe-browser/scripts/visual-diff.js --name homepage --update-baseline
Baselines live in .aqe/visual-baselines/. The script uses pixelmatch when installed, with a hash-based exact-match fallback otherwise. Non-zero exit when similarity < 1 - threshold, so CI gating is $?-based.
Use the Playwright recipe below only when you need:
import { test, expect } from '@playwright/test';
test('homepage visual regression', async ({ page }) => {
await page.goto('https://example.com');
// Capture and compare screenshot
await expect(page).toHaveScreenshot('homepage.png');
// First run: saves baseline
// Subsequent runs: compares to baseline
});
test('responsive design', async ({ page }) => {
// Mobile viewport
await page.setViewportSize({ width: 375, height: 667 });
await page.goto('https://example.com');
await expect(page).toHaveScreenshot('homepage-mobile.png');
// Tablet viewport
await page.setViewportSize({ width: 768, height: 1024 });
await expect(page).toHaveScreenshot('homepage-tablet.png');
});
test('mask dynamic elements', async ({ page }) => {
await page.goto('https://example.com');
await expect(page).toHaveScreenshot({
mask: [
page.locator('.timestamp'), // Dynamic time
page.locator('.user-count'), // Live counter
page.locator('.advertisement'), // Ads
page.locator('.avatar') // User avatars
]
});
});
import percySnapshot from '@percy/playwright';
test('AI-powered visual test', async ({ page }) => {
await page.goto('https://example.com');
// Percy uses AI to ignore anti-aliasing, minor font differences
await percySnapshot(page, 'Homepage');
});
test('component visual test', async ({ page }) => {
await page.goto('https://example.com/components');
// Snapshot specific component
const button = page.locator('.primary-button');
await percySnapshot(page, 'Primary Button', {
scope: button
});
});
// playwright.config.js
export default {
expect: {
toHaveScreenshot: {
maxDiffPixels: 100, // Allow 100 pixel difference
maxDiffPixelRatio: 0.01, // Or 1% of image
threshold: 0.2, // Color similarity threshold
animations: 'disabled', // Disable animations
caret: 'hide' // Hide cursor
}
}
};
// Comprehensive visual regression
await Task("Visual Regression Suite", {
baseline: 'main-branch',
current: 'feature-branch',
pages: ['homepage', 'product', 'checkout'],
devices: ['desktop', 'tablet', 'mobile'],
browsers: ['chrome', 'firefox', 'safari'],
threshold: 0.01
}, "qe-visual-tester");
// Returns:
// {
// comparisons: 27, // 3 pages × 3 devices × 3 browsers
// differences: 2,
// report: 'visual-regression-report.html'
// }
aqe/visual-testing/
├── baselines/* - Baseline screenshots
├── comparisons/* - Diff results
├── components/* - Component snapshots
└── reports/* - Visual regression reports
const visualFleet = await FleetManager.coordinate({
strategy: 'visual-testing',
agents: [
'qe-visual-tester', // Screenshot comparison
'qe-test-executor', // Cross-browser execution
'qe-quality-gate' // Block on visual regressions
],
topology: 'parallel'
});
Functional tests don't catch visual bugs. Layout shifts, color changes, font rendering, alignment issues - all invisible to functional tests but visible to users.
AI-powered tools reduce false positives. Percy, Applitools use AI to ignore insignificant differences (anti-aliasing, minor font rendering).
With Agents: qe-visual-tester automates visual regression across browsers and devices, uses AI to filter noise, and generates visual diff reports. Catches UI regressions before users see them.
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Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
日本語の概要は準備中です。原文の説明を表示しています。
WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
日本語の概要は準備中です。原文の説明を表示しています。