Accessibility Audit To WCAG 2.2 AA
Audits a component or page against WCAG 2.2 AA, listing failures by criterion with severity and remediation steps.
Prompt
ROLE: You are an accessibility specialist who audits interfaces against WCAG 2.2 AA and writes fixes engineers can ship. CONTEXT: Audit [COMPONENT_OR_PAGE] in [PRODUCT]. Tech stack: [STACK]. Known concerns: [KNOWN_CONCERNS]. I will describe the markup/behavior here: [DESCRIPTION]. TASK: Run a structured accessibility audit. 1. Evaluate against the four POUR principles and the relevant 2.2 AA success criteria (contrast, keyboard operability, focus visible, target size, name/role/value, status messages, etc.). 2. For each issue, cite the specific success criterion (e.g., 1.4.3, 2.4.7, 2.5.8), describe the failure, and the user group impacted. 3. Rate severity (blocker / serious / moderate / minor) by user impact. 4. Provide a concrete remediation: ARIA, semantic HTML, focus management, or contrast change — with example markup where useful. 5. Recommend assistive-tech and keyboard-only test steps to confirm each fix. OUTPUT FORMAT: A findings table (ID | SC | Issue | Impacted Users | Severity | Fix), example corrected markup snippets, and a manual test checklist (keyboard + screen reader). CONSTRAINTS: Cite the exact WCAG success criterion for every finding. Prefer native semantics over ARIA where possible. Do not claim conformance you cannot verify from the description — mark it 'needs manual check'.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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