Run eight automated canvas checks for potential accessibility issues, navigate each finding in Framer, and use the AI alt-text fixer to draft descriptions for images you explicitly select. Complete manual testing before you publish.
Find common canvas-level accessibility problems earlier, then review every result in context before client handoff.
Detects images without alternative text. For images you select, AI drafts a description using your own API key; you review it before applying the change.
Flags missing H1s, skipped heading levels, and large text that may need a semantic heading style.
Finds interactive elements that lack visible text labels — icon-only buttons and empty links that screen readers can't announce.
Calculates text contrast on supported solid backgrounds and flags gradients, images, and variable backgrounds for manual review.
Select all flagged elements on canvas at once. See every issue highlighted in context — no more hunting node by node.
Step through issues one by one with Next/Previous buttons — like "Next Error" in an IDE. Triage accessibility problems in seconds.
Start with automated canvas findings in Framer, then complete the manual checks that automation cannot cover.
Click "Run Audit" to run eight automated checks across images, headings, links, contrast, touch targets, typography, ARIA suggestions, and focus order.
Browse issues by category — click any issue to zoom directly to the problematic element on canvas.
Use AI to draft alt text for selected images. Resolve heading and contrast findings manually in Framer, re-run the checks, and document the remaining manual tests.
Run accessibility QA on your Framer canvas before client handoff.
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