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Rgaa Images

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MTeelokee
rgaa-images

Audit a web page for RGAA v4.1.2 Theme 1 – Images accessibility compliance. Checks that informative images have text alternatives, decorative images are correctly hidden, alternatives are relevant, CAPTCHAs have alternative access, detailed descriptions exist when needed, text images are avoided, and captions are properly linked. Use this skill whenever someone asks to check, audit, or verify image accessibility on a website, or when they mention RGAA images, alt text audit, or image accessibility compliance.

Overview

PublisherMTeelokee
Repositoryrgaa-accessibility-audit
Skill namergaa-images
Stars
6
Forks
1
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by MTeelokee on GitHub. Read the source before you install it.

Installation

Install the Rgaa Images 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/MTeelokee/rgaa-accessibility-audit/tree/main/skills/rgaa-images
  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/MTeelokee/rgaa-accessibility-audit.git /tmp/rgaa-accessibility-audit
mkdir -p .claude/skills
cp -r /tmp/rgaa-accessibility-audit/skills/rgaa-images .claude/skills/rgaa-images
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rgaa Images 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 Rgaa Images 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 Rgaa Images 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.

RGAA Images Accessibility Audit (Theme 1)

This skill audits a web page against the 9 criteria of RGAA v4.1.2 Theme 1: Images.

When to use

Trigger this skill when the user asks to audit image accessibility on a web page, check alt texts, verify RGAA Theme 1 compliance, or any request related to image accessibility verification.

Prerequisites

You need access to the page via Claude in Chrome (read_page, get_page_text, javascript_tool). Make sure the target page is open in the browser before starting.

Audit procedure

Step 1: Gather page data

Use javascript_tool to extract all image-related elements from the page:

javascript
(() => {
  const results = { imgs: [], areas: [], inputImages: [], svgs: [], objects: [], embeds: [], canvas: [], roleImgs: [], iframes: [] };

  // <img> tags
  document.querySelectorAll('img').forEach(el => {
    results.imgs.push({
      src: el.src?.substring(0, 100),
      alt: el.getAttribute('alt'),
      title: el.getAttribute('title'),
      ariaLabel: el.getAttribute('aria-label'),
      ariaLabelledby: el.getAttribute('aria-labelledby'),
      ariaHidden: el.getAttribute('aria-hidden'),
      role: el.getAttribute('role'),
      hasParentFigure: !!el.closest('figure'),
      parentFigureAriaLabel: el.closest('figure')?.getAttribute('aria-label'),
      hasFigcaption: !!el.closest('figure')?.querySelector('figcaption'),
      width: el.naturalWidth,
      height: el.naturalHeight
    });
  });

  // elements with role="img"
  document.querySelectorAll('[role="img"]').forEach(el => {
    if (el.tagName !== 'IMG') {
      results.roleImgs.push({
        tag: el.tagName.toLowerCase(),
        ariaLabel: el.getAttribute('aria-label'),
        ariaLabelledby: el.getAttribute('aria-labelledby'),
        textContent: el.textContent?.substring(0, 100)
      });
    }
  });

  // <svg> tags
  document.querySelectorAll('svg').forEach(el => {
    results.svgs.push({
      role: el.getAttribute('role'),
      ariaLabel: el.getAttribute('aria-label'),
      ariaLabelledby: el.getAttribute('aria-labelledby'),
      ariaHidden: el.getAttribute('aria-hidden'),
      hasTitle: !!el.querySelector('title'),
      titleContent: el.querySelector('title')?.textContent,
      hasDesc: !!el.querySelector('desc'),
      descContent: el.querySelector('desc')?.textContent
    });
  });

  // <area> tags
  document.querySelectorAll('area').forEach(el => {
    results.areas.push({
      href: el.getAttribute('href'),
      alt: el.getAttribute('alt'),
      ariaLabel: el.getAttribute('aria-label')
    });
  });

  // <input type="image">
  document.querySelectorAll('input[type="image"]').forEach(el => {
    results.inputImages.push({
      alt: el.getAttribute('alt'),
      title: el.getAttribute('title'),
      ariaLabel: el.getAttribute('aria-label'),
      src: el.src?.substring(0, 100)
    });
  });

  // <object type="image/...">
  document.querySelectorAll('object[type^="image"]').forEach(el => {
    results.objects.push({
      type: el.type,
      role: el.getAttribute('role'),
      ariaLabel: el.getAttribute('aria-label'),
      ariaHidden: el.getAttribute('aria-hidden')
    });
  });

  // <embed type="image/...">
  document.querySelectorAll('embed[type^="image"]').forEach(el => {
    results.embeds.push({
      type: el.type,
      role: el.getAttribute('role'),
      ariaLabel: el.getAttribute('aria-label'),
      ariaHidden: el.getAttribute('aria-hidden')
    });
  });

  // <canvas>
  document.querySelectorAll('canvas').forEach(el => {
    results.canvas.push({
      role: el.getAttribute('role'),
      ariaLabel: el.getAttribute('aria-label'),
      ariaHidden: el.getAttribute('aria-hidden'),
      fallbackContent: el.textContent?.trim().substring(0, 100)
    });
  });

  return JSON.stringify(results, null, 2);
})()

Step 2: Evaluate each criterion

For each criterion, read the detailed checks from references/criteria.md and apply them to the collected data.

Criterion 1.1 – Informative images must have a text alternative. Check every <img>, <area>, <input type="image">, <svg>, <object>, <embed>, <canvas>, and [role="img"] element. If the image conveys information (not decorative), it must have an alt, aria-label, aria-labelledby, or title attribute.

Criterion 1.2 – Decorative images must be ignored by assistive technologies. Decorative <img> must have alt="" and no other text alternative, OR aria-hidden="true" / role="presentation". Decorative <svg> must have aria-hidden="true" and no <title> or <desc>.

Criterion 1.3 – Text alternatives must be relevant. When an informative image has an alt text, check that it actually describes the image content meaningfully, not just "image" or a filename.

Criterion 1.4 – CAPTCHA/test images must identify their nature. If a CAPTCHA is present, its alternative should say it is a CAPTCHA and describe its function, not its content.

Criterion 1.5 – CAPTCHAs must have an alternative access method. If a graphical CAPTCHA exists, verify there is at least one alternative (audio, logic, etc.).

Criterion 1.6 – Informative images needing a detailed description must have one. Complex images (charts, infographics) need a longdesc, adjacent link, or aria-describedby pointing to a detailed description.

Criterion 1.7 – Detailed descriptions must be relevant. If a detailed description exists, verify its content is accurate and complete.

Criterion 1.8 – Text images should be replaced with styled text when possible. Flag images that contain only text and could be replaced with CSS-styled HTML text (except logos, trademarks, CAPTCHAs).

Criterion 1.9 – Image captions must be correctly linked. Images with captions must use <figure> + <figcaption>, with role="figure" and aria-label matching the caption.

Step 3: Generate the report

Produce a structured report with:

  • A summary score (number of criteria passed / total applicable)
  • For each criterion: status (✅ Passed, ❌ Failed, ⚠️ Warning, N/A), the elements concerned, and recommendations to fix issues
  • An overall compliance assessment for Theme 1

Important notes

  • Distinguishing informative from decorative images requires human judgment. Flag ambiguous cases as warnings.
  • Alt text relevance is subjective — flag clearly bad alternatives (empty on informative images, filenames, "image", "photo") but note that full relevance assessment may need human review.
  • Some tests (like 1.8 on text images) require visual inspection. Use screenshots when needed.

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 Rgaa Images AI skill do?

Audit a web page for RGAA v4.1.2 Theme 1 – Images accessibility compliance. Checks that informative images have text alternatives, decorative images are correctly hidden, alternatives are relevant, CAPTCHAs have alternative access, detailed descriptions exist when needed, text images are avoided, and captions are properly linked. Use this skill whenever someone asks to check, audit, or verify image accessibility on a website, or when they mention RGAA images, alt text audit, or image accessibility compliance.

Why use Rgaa Images on TypingMind?

Because you install it once and use it with any model. Rgaa Images 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 Rgaa Images in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MTeelokee/rgaa-accessibility-audit/tree/main/skills/rgaa-images. 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 Rgaa Images?

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 Rgaa Images?

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

Is the Rgaa Images AI skill free?

Yes. It is published on GitHub by MTeelokee 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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