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/description consistent 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 →