Validate JSON-LD templates tuned for how AI assistants extract and cite information. Zero dependencies.
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schema-for-ai
Copy-paste JSON-LD templates tuned for how AI assistants extract and cite information. Structured data helps ChatGPT, Perplexity, Gemini, and Google AI resolve what your product is and pull clean facts into answers — instead of guessing from raw HTML.
- Ready-to-edit templates for the schema types that matter most for AEO.
- A tiny
validate.py(stdlib only) to sanity-check your JSON-LD. - Notes on why each one helps AI extraction.
Drop a template in a <script type="application/ld+json">…</script> tag in your
page <head>, replace the {{placeholders}}, and validate.
Why structured data helps AI answers
LLM answers lean heavily on entities (is "Acme" a company? a product? which
one?) and on extractable facts (price, category, FAQ answers). JSON-LD states
those explicitly and unambiguously, which makes you easier to identify, trust, and
quote. Pair it with a clean llms.txt (see our
llms-txt-generator).
Validate
python validate.py mypage.jsonld
Checks valid JSON, the presence of @context/@type, and warns about missing
recommended fields for common types.
Templates
Organization
Establishes the entity. Put it on your homepage.
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "{{Company Name}}",
"url": "https://{{domain}}",
"logo": "https://{{domain}}/logo.png",
"description": "{{One sentence on what you do and for whom}}",
"sameAs": [
"https://www.linkedin.com/company/{{handle}}",
"https://x.com/{{handle}}",
"https://www.crunchbase.com/organization/{{handle}}"
]
}
SoftwareApplication / Product
For a tool or product page — gives AI the category, price, and ratings.
{
"@context": "https://schema.org",
"@type": "SoftwareApplication",
"name": "{{Product Name}}",
"applicationCategory": "{{e.g. DeveloperApplication}}",
"operatingSystem": "{{e.g. Web, macOS, Linux}}",
"description": "{{What it does, for whom, key differentiator}}",
"offers": {
"@type": "Offer",
"price": "{{0.00}}",
"priceCurrency": "{{USD}}"
}
}
FAQPage
AI loves FAQs — short Q/A pairs are highly extractable. Mark up real questions buyers ask.
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "{{A real question a buyer asks}}",
"acceptedAnswer": {
"@type": "Answer",
"text": "{{A clear, self-contained answer in 1–3 sentences}}"
}
}
]
}
Article / BlogPosting
For blog posts — author, date, and headline help AI attribute and cite you.
{
"@context": "https://schema.org",
"@type": "BlogPosting",
"headline": "{{Post title}}",
"datePublished": "{{2026-01-01}}",
"author": { "@type": "Person", "name": "{{Author}}" },
"publisher": { "@type": "Organization", "name": "{{Company Name}}" },
"description": "{{One-line summary}}"
}
BreadcrumbList
Helps AI understand your site structure and the page's place in it.
{
"@context": "https://schema.org",
"@type": "BreadcrumbList",
"itemListElement": [
{ "@type": "ListItem", "position": 1, "name": "Home", "item": "https://{{domain}}/" },
{ "@type": "ListItem", "position": 2, "name": "{{Section}}", "item": "https://{{domain}}/{{section}}/" }
]
}
Tips
- One entity per page; keep
name/descriptionconsistent everywhere (consistency is an entity signal). - Put real, useful FAQ answers — don't keyword-stuff. AI (and Google) penalize it.
- Validate before shipping; a broken JSON-LD block is ignored entirely.
License
MIT © Clear Cited
Built by Clear Cited — AEO/GEO for B2B SaaS & developer tools. See if AI recommends your product →
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