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Accessibility Testing Strategy

Community
Owl-Listener
accessibility-testing-strategy

Plan what to test, how to test, and who should test for accessibility. Use when defining a testing approach, planning QA, setting up automated and manual testing, or deciding what level of accessibility testing a project needs. Triggers on: accessibility testing, how to test, test plan, automated testing, manual testing, screen reader testing, user testing, accessibility QA, what to test, testing strategy.

Overview

PublisherOwl-Listener
Repositoryinclusive-design-skills
Skill nameaccessibility-testing-strategy
Stars
108
Forks
28
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Owl-Listener on GitHub. Read the source before you install it.

Installation

Install the Accessibility Testing Strategy 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.
    https://github.com/Owl-Listener/inclusive-design-skills/tree/main/accessibility-decisions/skills/accessibility-testing-strategy
  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/Owl-Listener/inclusive-design-skills.git /tmp/inclusive-design-skills
mkdir -p .claude/skills
cp -r /tmp/inclusive-design-skills/accessibility-decisions/skills/accessibility-testing-strategy .claude/skills/accessibility-testing-strategy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Accessibility Testing Strategy 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 Strategy 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 Strategy 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 Strategy

Plan a testing approach that catches real accessibility barriers — because automated tools find roughly 30% of issues. The other 70% require human judgment.

The Testing Pyramid

Layer 1: Automated Testing (Catches ~30%)

What it finds:

  • Missing alt text
  • Colour contrast failures
  • Missing form labels
  • Missing language attribute
  • Empty headings and buttons
  • Duplicate IDs

What it misses:

  • Whether alt text is meaningful
  • Whether focus order is logical
  • Whether content makes sense
  • Whether interactions work with keyboard
  • Whether the experience is usable

Tools: axe, Lighthouse, WAVE, Pa11y, jest-axe When: on every build, in CI/CD pipeline Who: automated — no human needed

Layer 2: Manual Expert Testing (Catches ~50%)

What it finds:

  • Keyboard navigation issues
  • Focus management problems
  • Logical reading order failures
  • Meaningful alt text assessment
  • Cognitive accessibility barriers
  • Interaction pattern issues

Method:

  • Tab through every interactive element
  • Test with screen reader (VoiceOver or NVDA)
  • Test at 200% zoom
  • Test with system preferences enabled
  • Review content for plain language

When: before each release, on major feature changes Who: someone trained in accessibility testing

Layer 3: User Testing With Disabled People (Catches remaining ~20%)

What it finds:

  • Real-world usability barriers that experts miss
  • Assistive technology compatibility issues
  • Unexpected workflows and workarounds
  • Cognitive and emotional barriers
  • Issues that only appear with actual AT proficiency

Method:

  • Recruit participants with diverse disabilities
  • Test core tasks with their own devices and AT
  • Observe — don't guide or explain
  • Record what works, what fails, and what frustrates

When: quarterly, or before major launches Who: users with disabilities using their own setup

What to Test First

Priority 1: Core Tasks

  • Can users complete the primary tasks the product exists for?
  • Test the critical path end to end
  • Any failure here is a launch blocker

Priority 2: Input and Navigation

  • Keyboard-only navigation through the core flow
  • Screen reader navigation through the core flow
  • Touch interaction on mobile for the core flow

Priority 3: Content and Comprehension

  • Is content understandable at the target reading level?
  • Are error messages helpful?
  • Is help available and findable?

Priority 4: Edge Cases and Preferences

  • Zoom to 200%
  • System preferences (reduced motion, high contrast, dark mode)
  • Long content, empty states, error states

Screen Reader Testing Basics

For teams new to screen reader testing:

Start With VoiceOver (Mac)

  • Turn on: Cmd + F5
  • Navigate: VO + arrow keys (VO = Ctrl + Option)
  • Headings: VO + Cmd + H
  • Links: VO + Cmd + L
  • Forms: VO + Cmd + J
  • Turn off: Cmd + F5

Start With NVDA (Windows)

  • Download free from nvaccess.org
  • Navigate: Tab, arrow keys
  • Headings: H
  • Links: K
  • Forms: F
  • Stop speech: Ctrl

What to Listen For

  • Does every interactive element have a name?
  • Are state changes announced (expanded, selected, checked)?
  • Does focus move to the right place after actions?
  • Can you understand the page reading only the headings?

Assessment Questions

  1. Is automated testing running on every build?
  2. Is manual expert testing happening before each release?
  3. Has the product been tested by people with disabilities?
  4. Are core tasks tested with keyboard and screen reader?
  5. Is there a clear priority for what to test first?

Frequently asked questions

What does the Accessibility Testing Strategy AI skill do?

Plan what to test, how to test, and who should test for accessibility. Use when defining a testing approach, planning QA, setting up automated and manual testing, or deciding what level of accessibility testing a project needs. Triggers on: accessibility testing, how to test, test plan, automated testing, manual testing, screen reader testing, user testing, accessibility QA, what to test, testing strategy.

Why use Accessibility Testing Strategy on TypingMind?

Because you install it once and use it with any model. Accessibility Testing Strategy 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 Strategy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Owl-Listener/inclusive-design-skills/tree/main/accessibility-decisions/skills/accessibility-testing-strategy. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Accessibility Testing Strategy?

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 Strategy?

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

Is the Accessibility Testing Strategy AI skill free?

Yes. It is published on GitHub by Owl-Listener 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.

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