> browser-qa
# Browser QA — Automated Visual Testing & Interaction ## When to Use - After deploying a feature to staging/preview - When you need to verify UI behavior across pages - Before shipping — confirm layouts, forms, interactions actually work - When reviewing PRs that touch frontend code - Accessibility audits and responsive testing ## How It Works Uses the browser automation MCP (claude-in-chrome, Playwright, or Puppeteer) to interact with live pages like a real user. ### Phase 1: Smoke Test ``
curl "https://skillshub.wtf/affaan-m/everything-claude-code/browser-qa?format=md"Browser QA — Automated Visual Testing & Interaction
When to Use
- After deploying a feature to staging/preview
- When you need to verify UI behavior across pages
- Before shipping — confirm layouts, forms, interactions actually work
- When reviewing PRs that touch frontend code
- Accessibility audits and responsive testing
How It Works
Uses the browser automation MCP (claude-in-chrome, Playwright, or Puppeteer) to interact with live pages like a real user.
Phase 1: Smoke Test
1. Navigate to target URL
2. Check for console errors (filter noise: analytics, third-party)
3. Verify no 4xx/5xx in network requests
4. Screenshot above-the-fold on desktop + mobile viewport
5. Check Core Web Vitals: LCP < 2.5s, CLS < 0.1, INP < 200ms
Phase 2: Interaction Test
1. Click every nav link — verify no dead links
2. Submit forms with valid data — verify success state
3. Submit forms with invalid data — verify error state
4. Test auth flow: login → protected page → logout
5. Test critical user journeys (checkout, onboarding, search)
Phase 3: Visual Regression
1. Screenshot key pages at 3 breakpoints (375px, 768px, 1440px)
2. Compare against baseline screenshots (if stored)
3. Flag layout shifts > 5px, missing elements, overflow
4. Check dark mode if applicable
Phase 4: Accessibility
1. Run axe-core or equivalent on each page
2. Flag WCAG AA violations (contrast, labels, focus order)
3. Verify keyboard navigation works end-to-end
4. Check screen reader landmarks
Output Format
## QA Report — [URL] — [timestamp]
### Smoke Test
- Console errors: 0 critical, 2 warnings (analytics noise)
- Network: all 200/304, no failures
- Core Web Vitals: LCP 1.2s ✓, CLS 0.02 ✓, INP 89ms ✓
### Interactions
- [✓] Nav links: 12/12 working
- [✗] Contact form: missing error state for invalid email
- [✓] Auth flow: login/logout working
### Visual
- [✗] Hero section overflows on 375px viewport
- [✓] Dark mode: all pages consistent
### Accessibility
- 2 AA violations: missing alt text on hero image, low contrast on footer links
### Verdict: SHIP WITH FIXES (2 issues, 0 blockers)
Integration
Works with any browser MCP:
mChild__claude-in-chrome__*tools (preferred — uses your actual Chrome)- Playwright via
mcp__browserbase__* - Direct Puppeteer scripts
Pair with /canary-watch for post-deploy monitoring.
> related_skills --same-repo
> skill-comply
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines
> santa-method
Multi-agent adversarial verification with convergence loop. Two independent review agents must both pass before output ships.
> safety-guard
# Safety Guard — Prevent Destructive Operations ## When to Use - When working on production systems - When agents are running autonomously (full-auto mode) - When you want to restrict edits to a specific directory - During sensitive operations (migrations, deploys, data changes) ## How It Works Three modes of protection: ### Mode 1: Careful Mode Intercepts destructive commands before execution and warns: ``` Watched patterns: - rm -rf (especially /, ~, or project root) - git push --force
> product-lens
# Product Lens — Think Before You Build ## When to Use - Before starting any feature — validate the "why" - Weekly product review — are we building the right thing? - When stuck choosing between features - Before a launch — sanity check the user journey - When converting a vague idea into a spec ## How It Works ### Mode 1: Product Diagnostic Like YC office hours but automated. Asks the hard questions: ``` 1. Who is this for? (specific person, not "developers") 2. What's the pain? (quantify