Free tool · No signup · Last updated 2026-05-22
Free FAQ schema generator. Generate valid JSON-LD FAQPage markup with Question and AcceptedAnswer pairs. The highest-cited schema type by AI answer engines.
FAQPage schema marks a page as a list of questions and accepted answers. Of all schema types tracked by BrandCited across AI engine citations, FAQPage is the single most-cited — AI Overviews, ChatGPT, Perplexity, Claude all extract Question/Answer pairs verbatim when responding to user queries that mirror the question. A well-built FAQPage is a citation-extraction surface, not just a UI accordion.
These are the minimum properties for a valid FAQPage schema block. The generator marks each with a red asterisk in the form.
| Field | What goes here |
|---|---|
| mainEntity | Array of Question objects (must have at least 1, Google recommends 6-10). |
| Question.name | The full question text as a user would phrase it. |
| Question.acceptedAnswer | The single canonical answer (an Answer object). |
| Answer.text | The answer text. 40-100 words is the sweet spot for AI extraction. |
Optional fields add richness without breaking validation. The ones below have measurable impact on AI engine extraction.
| Field | Why add it |
|---|---|
| about | Reference to the parent entity the FAQ is about (Organization, Product, Service). |
| inLanguage | BCP 47 language code. Default: en. |
AI visibility note
FAQPage is disproportionately cited because the schema format (question + answer pair) perfectly matches the question-answer shape of AI engine queries. When a user asks ChatGPT "how does X work" and your FAQPage has a Question with that exact phrasing + a concise AcceptedAnswer, your answer text gets pulled almost verbatim. Pages with 8-12 well-targeted Q&A pairs outperform pages with the same content in unstructured prose.
Here's what a complete FAQPage block looks like when generated from the tool. Copy and adapt to your data.
Example JSON-LD
Validates against Google Rich Results
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What is BrandCited?",
"acceptedAnswer": {
"@type": "Answer",
"text": "BrandCited is an AI visibility platform that tracks how ChatGPT, Claude, Gemini, Perplexity, and 5 other AI engines cite your brand. It runs site audits, monitors citation share-of-voice, and returns a prioritized fix plan."
}
},
{
"@type": "Question",
"name": "How much does BrandCited cost?",
"acceptedAnswer": {
"@type": "Answer",
"text": "BrandCited has a permanent free tier including 1 scan per month across all 9 AI engines. Paid plans start at $39/month (Starter) and scale to $299/month (Agency) with white-label reports and API access." // lint-no-hardcoded-counts:allow — illustrative example inside FAQPage JSON-LD string literal
}
}
]
}Minimum 1, but Google rich-result eligibility is strongest at 6-10. AI engines extract from any count, but pages with 8-12 substantive Q&As across genuinely distinct query shapes outperform sparser pages. More than 15 starts to dilute — split into multiple themed FAQ pages instead.
40-100 words is the sweet spot for AI extraction. Below 40 words the answer is too thin to pull as a quote; above 150 it gets truncated. Lead with the direct answer in the first 1-2 sentences and add nuance after.
Yes, and you should. Each page should have FAQ schema for questions specific to that page's topic. Repeating the same FAQs site-wide creates duplicate signals that AI engines deduplicate — different pages with topic-specific FAQs cover more query shapes.
Yes — exactly. Use Google's People Also Ask box, AnswerThePublic, or your site search analytics to find the literal phrasings users search. Match the Question.name to those phrasings; the AcceptedAnswer.text gets cited verbatim when those exact queries hit AI engines.
Cite this tool
BrandCited FAQPage Schema Generator. (2026). https://www.brandcited.ai/tools/schema-generator/faqpage
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