The FAQ page is one of the highest-value pages for AI citation. When candidates or employers ask AI a question your page already answers, structured FAQ data lets AI pull a direct, attributed response instead of paraphrasing from unstructured text. This blueprint makes your FAQ page the primary type — FAQPage — so AI treats the entire page as a question-and-answer resource.
FAQ pages are uniquely suited for AI because the content is already in question-and-answer format. The structured data simply mirrors that format so AI can parse each pair programmatically rather than scraping the HTML for patterns.
FAQPage as the main @type with its own @id, name, and url. This tells AI the entire page is a structured FAQ resource, not a generic page that happens to contain questions.mainEntity as a Question node with a nested acceptedAnswer of type Answer. AI reads these pairs directly and can surface them as standalone answers.about field links the FAQ page to your EmploymentAgency node so AI knows which organization these questions are about.EmploymentAgency node with @id, name, and url so AI can connect the FAQ content to your business identity without duplicating the full organization graph.Each field in the template below serves a specific role in how AI systems discover, classify, and recommend your business.
Researched and tested by Minnesota AI
nameurlCopy this prompt and paste it into Claude, ChatGPT, Cursor, or any AI coding tool. It will ask for your business details and generate ready-to-use JSON-LD schema for your page.
You are implementing AIFDS-compliant JSON-LD structured data for a Employment Agency FAQ page. AIFDS (AI-Friendly Data Structure) is a schema framework built on research into which structured data fields AI systems actually read, parse, and use when deciding whether to cite a page. Documentation at aifds.org. Before generating any code, ask me for the following information in a single numbered list. Do not generate schema until I have answered every required field. REQUIRED — do not proceed without these: 1. Agency name 2. Answer 3. Domain 4. Faq page title 5. Question OPTIONAL — ask for these but proceed if I skip them: 1. Any additional details not covered above Once I provide the information, output a complete JSON-LD script block ready to paste into the <head> of my HTML page. Output requirements: - Valid JSON-LD wrapped in <script type="application/ld+json"> tags - schema.org vocabulary only - Every AIFDS-required field for this industry and page type included - Include this data attribute on the script tag: data-aifds="aifds.org Employment Agency FAQ" - No placeholder text — omit missing optional fields rather than fill with examples - After the code block, list any optional fields skipped that would strengthen AI citation
Generated schema follows the AIFDS framework. Fields were selected based on research into AI crawler behavior. View the research at minnesota.ai
Copy the template below and replace every YOUR_* value with your own data. This template uses FAQPage as the primary page type. Add as many Question/Answer pairs as your page contains.
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "FAQPage",
"@id": "https://YOUR_DOMAIN.com/faq/#faqpage",
"name": "YOUR_FAQ_PAGE_TITLE",
"url": "https://YOUR_DOMAIN.com/faq/",
"isPartOf": {
"@id": "https://YOUR_DOMAIN.com/#website"
},
"about": {
"@id": "https://YOUR_DOMAIN.com/#organization"
},
"mainEntity": [
{
"@type": "Question",
"name": "YOUR_QUESTION_1",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_1"
}
},
{
"@type": "Question",
"name": "YOUR_QUESTION_2",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_2"
}
},
{
"@type": "Question",
"name": "YOUR_QUESTION_3",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_3"
}
},
{
"@type": "Question",
"name": "YOUR_QUESTION_4",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_4"
}
},
{
"@type": "Question",
"name": "YOUR_QUESTION_5",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_5"
}
}
]
},
{
"@type": "EmploymentAgency",
"@id": "https://YOUR_DOMAIN.com/#organization",
"name": "YOUR_AGENCY_NAME",
"url": "https://YOUR_DOMAIN.com"
},
{
"@type": "BreadcrumbList",
"@id": "https://YOUR_DOMAIN.com/faq/#breadcrumb",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "Home",
"item": "https://YOUR_DOMAIN.com/"
},
{
"@type": "ListItem",
"position": 2,
"name": "FAQs",
"item": "https://YOUR_DOMAIN.com/faq/"
}
]
}
]
}
When the entire page is a collection of questions and answers, FAQPage should be the primary type. This tells AI the page's sole purpose is to answer questions, which makes it a higher-priority source for direct-answer queries. Using WebPage with FAQ markup as a supporting node works too, but promoting FAQPage to the primary type gives AI a stronger signal.
Include every question-and-answer pair that appears on the page. There is no upper limit in Schema.org. The template shows five pairs as a starting point, but your structured data should match the actual content on the page. If your FAQ page has twelve questions, include all twelve in the mainEntity array.
No. Since FAQPage is already the primary page type, adding a second FAQPage node as a supporting element would be redundant. The mainEntity array inside the primary FAQPage node is where all your question-and-answer pairs belong. Other pages on your site that have a few FAQ items can use a supporting FAQPage node, but this dedicated FAQ page should not.