JSON-LD Organization, Product, FAQ schema — generated and validated.
Schema.org markup is how AI models confirm what they think they know. Build it cleanly. We output the three types that matter most, validated against Google Rich Results.
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Christmas or Not",
"url": "https://christmasornot.com",
"logo": "https://christmasornot.com/logo.png",
"description": "Christmas or Not is a single-purpose web service that tells you whether today is December 25.",
"foundingDate": "2019-12-01",
"address": {
"@type": "PostalAddress",
"addressCountry": "US"
},
"sameAs": [
"https://twitter.com/christmasornot",
"https://github.com/christmasornot"
],
"contactPoint": {
"@type": "ContactPoint",
"email": "hello@christmasornot.com",
"contactType": "customer support"
}
}We'll email the schema plus a one-page guide on where to drop it, how to validate after deploy, and which fields models actually read in 2026.
Three types. Different use cases.
Not every page needs every schema. Use the right type for the right surface — models reward precision and punish stuffing.
Organization
The atomic identity card for your brand. Name, URL, logo, founding date, contact, social profiles. Read by every model. Drop it on your homepage and About page.
Product
Per-product structured data. Price, currency, availability, reviews, brand. Critical for e-commerce — and for AI shopping agents that route purchase intent.
FAQ
Question–answer pairs in machine-readable form. The fastest way to seed responses to known prospect questions. Pulls into Google AI Overview and Perplexity answers.