FAQ Schema Generator
Paste your FAQ or article text, or fetch it straight from a URL, and get ready-to-use FAQPage JSON-LD schema instantly.
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": []
}
</script>About this tool
This tool scans your text line by line, whether pasted directly or fetched from a URL, and treats any line that ends in a question mark as a question, then attaches the lines under it as the answer, up until the next question. It understands plain FAQ lists, "Q:"/"A:" labels, numbered and bulleted lists, and basic HTML, and it strips that formatting automatically. Markdown headings ("## What is X?") are treated as section structure rather than questions by default, since most real headings are document labels, not literal FAQ entries. If your FAQ genuinely uses one heading per question, a toggle appears to include them. Same-line pairs like "Q? A." on a single line are not supported: put the question and its answer on separate lines for reliable detection.
As of August 2026, Google no longer shows FAQ rich results (the expandable dropdown snippet) in Search for any site, a change it made permanent on May 7, 2026. The FAQPage schema type itself is still fully valid, and Google has said there's no need to remove existing markup, it simply no longer triggers that particular visual result. What the schema still does well is give search engines and AI systems, including ChatGPT, Perplexity, and Google's AI Overviews, an unambiguous, pre-structured question-answer pairing to cite from, instead of one they have to infer from surrounding prose. Writing tight, well-paired Q&A content is also good practice for AI-answer visibility on its own, independent of the schema.
Before publishing the generated code, keep three things in mind: the same questions and answers should also be visible as real text on your page, not just present in the schema; avoid pasting the identical FAQ block onto many pages, since duplicated schema across a site can read as a manipulation signal; and a focused set of genuinely useful questions works better than padding the count; most guidance points to roughly 3 to 10 well-chosen questions per page.