Accessibility Testing logo

Accessibility Testing

Community
proffesor-for-testing
accessibility-testing

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.

Overview

Publisherproffesor-for-testing
Repositoryagentic-qe
Skill nameaccessibility-testing
Stars
480
Forks
92
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by proffesor-for-testing on GitHub. Read the source before you install it.

Installation

Install the Accessibility Testing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git /tmp/agentic-qe
mkdir -p .claude/skills
cp -r /tmp/agentic-qe/assets/skills/accessibility-testing .claude/skills/accessibility-testing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Accessibility Testing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Accessibility Testing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Accessibility Testing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Accessibility Testing

Consolidated: For comprehensive WCAG auditing with multi-tool testing (axe-core + pa11y + Lighthouse), video accessibility, and remediation, prefer /a11y-ally. This skill provides a quick reference card for basic accessibility testing patterns.

Browser engine

Browser-driven a11y checks should go through the qe-browser fleet skill. vibium a11y-tree --json returns the full accessibility tree without visual rendering — feed it into axe-core via vibium eval --stdin for ruleset enforcement. See .claude/skills/qe-browser/SKILL.md.

<default_to_action> When testing accessibility or ensuring compliance:

  1. APPLY POUR principles: Perceivable, Operable, Understandable, Robust
  2. TEST with keyboard-only navigation (Tab, Enter, Escape)
  3. VALIDATE with screen readers (VoiceOver, NVDA, JAWS)
  4. CHECK color contrast (4.5:1 for text, 3:1 for large text)
  5. AUTOMATE with axe-core, integrate in CI/CD pipeline

Quick A11y Checklist:

  • All images have alt text (or alt="" for decorative)
  • All form fields have labels
  • Color is never the only indicator
  • Focus visible on all interactive elements
  • Keyboard navigation works throughout

Critical Success Factors:

  • Automated testing catches 30-50% of issues
  • Manual testing with real assistive tech required
  • Include users with disabilities in testing </default_to_action>

Quick Reference Card

When to Use

  • Legal compliance (ADA, Section 508, EU Directive)
  • New feature development
  • Before release validation
  • Accessibility audits

WCAG 2.2 Levels

LevelRequirementTarget
ABasic accessibilityMinimum legal
AAStandard (most orgs)Industry standard
AAAEnhancedSpecialized sites

POUR Principles

PrincipleMeaningKey Tests
PerceivableCan perceive contentAlt text, contrast, captions
OperableCan operate UIKeyboard, no seizures, navigation
UnderstandableCan understandClear labels, predictable, errors
RobustWorks with assistive techValid HTML, ARIA

Color Contrast Requirements

ContentAA RatioAAA Ratio
Normal text4.5:17:1
Large text (18pt+)3:14.5:1
UI components3:1-

Keyboard Navigation Testing

javascript
// Test all interactive elements reachable via keyboard
test('all interactive elements keyboard accessible', async ({ page }) => {
  await page.goto('/');

  const focusableElements = await page.$$('button, a, input, select, textarea, [tabindex]');

  for (const element of focusableElements) {
    await element.focus();
    const isFocused = await element.evaluate(el => document.activeElement === el);
    expect(isFocused).toBe(true);
  }
});

// Verify visible focus indicator
test('focus indicator visible', async ({ page }) => {
  await page.goto('/');
  await page.keyboard.press('Tab');

  const focusedElement = await page.locator(':focus');
  const outline = await focusedElement.evaluate(el =>
    getComputedStyle(el).outline
  );

  expect(outline).not.toBe('none');
});

Automated Testing with axe-core

Preferred: via the a11y-ally AQE skill (qe-browser + Vibium)

For new work, use the a11y-ally skill — it composes qe-browser (Vibium WebDriver BiDi) with axe-core, pa11y, and Lighthouse and produces a WCAG-tagged JSON report with remediation guidance. It avoids the 300MB Playwright install and is already wired into the AQE fleet.

bash
# Runs axe-core + pa11y + Lighthouse via qe-browser (Vibium) engine
aqe skill run a11y-ally -- --url https://example.com --wcag AA

Fallback: Playwright + @axe-core/playwright

Keep this path when you have an existing Playwright suite and don't want to introduce a second browser runner, or when you need Firefox/Safari coverage that Vibium's Chrome-only BiDi backend can't provide today.

javascript
import { test, expect } from '@playwright/test';
import AxeBuilder from '@axe-core/playwright';

test('page has no accessibility violations', async ({ page }) => {
  await page.goto('/');

  const results = await new AxeBuilder({ page })
    .withTags(['wcag2a', 'wcag2aa', 'wcag22aa'])
    .analyze();

  expect(results.violations).toEqual([]);
});

// CI/CD integration
test('checkout flow accessible', async ({ page }) => {
  await page.goto('/checkout');

  const results = await new AxeBuilder({ page })
    .include('#checkout-form')
    .disableRules(['color-contrast']) // Fix in next sprint
    .analyze();

  expect(results.violations.filter(v =>
    v.impact === 'critical' || v.impact === 'serious'
  )).toHaveLength(0);
});

Screen Reader Testing Checklist

markdown
## VoiceOver (macOS) Testing
- [ ] Page title announced on load
- [ ] Headings hierarchy correct (h1 → h2 → h3)
- [ ] Landmarks present (nav, main, footer)
- [ ] Images have descriptive alt text
- [ ] Form labels read correctly
- [ ] Error messages announced
- [ ] Dynamic content updates announced (aria-live)

Agent-Driven Accessibility

typescript
// Comprehensive a11y validation
await Task("Accessibility Validation", {
  url: 'https://example.com/checkout',
  standard: 'WCAG2.2',
  level: 'AA',
  checks: ['keyboard', 'screen-reader', 'color-contrast'],
  includeScreenReaderSimulation: true
}, "qe-visual-tester");

// Fleet coordination for comprehensive testing
const a11yFleet = await FleetManager.coordinate({
  strategy: 'comprehensive-accessibility',
  agents: [
    'qe-visual-tester',     // Visual & keyboard checks
    'qe-test-generator',    // Generate a11y tests
    'qe-quality-gate'       // Enforce compliance
  ],
  topology: 'parallel'
});

Agent Coordination Hints

Memory Namespace

aqe/accessibility/
├── wcag-results/*       - WCAG audit results
├── screen-reader/*      - Screen reader test logs
├── remediation/*        - Fix recommendations
└── compliance/*         - Compliance reports

Fleet Coordination

typescript
const a11yFleet = await FleetManager.coordinate({
  strategy: 'accessibility-testing',
  agents: [
    'qe-visual-tester',   // axe-core, keyboard, focus
    'qe-test-generator',  // Generate a11y test cases
    'qe-quality-gate'     // Block non-compliant builds
  ],
  topology: 'parallel'
});

Related Skills


Remember

1 billion people have disabilities. Inaccessible software excludes 15% of humanity. Legal requirements: ADA, Section 508, EU Directive 2016/2102. $13T purchasing power. 250%+ increase in lawsuits.

Automated testing catches only 30-50% of issues. Combine with manual keyboard testing, screen reader testing, and real user testing with people with disabilities.

With Agents: Agents automate WCAG 2.2 compliance checking, screen reader simulation, and focus management validation. Use agents to enforce accessibility standards in CI/CD and catch violations before production.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Accessibility Testing AI skill do?

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.

Why use Accessibility Testing on TypingMind?

Because you install it once and use it with any model. Accessibility Testing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Accessibility Testing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/accessibility-testing. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Accessibility Testing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Accessibility Testing?

As many as you like. As long as a model supports skills, you can use Accessibility Testing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Accessibility Testing AI skill free?

Yes. It is published on GitHub by proffesor-for-testing under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇