---
title: "Schema JSON (JSON-LD) (schema.json)"
description: "Structured data, the way Google and AI engines prefer it."
canonical: "https://geordy.ai/formats/schema-json"
---
# Schema JSON (JSON-LD)

**Structured data, the way Google and AI engines prefer it.**

JSON-LD using schema.org vocabulary, page-typed automatically. Geordy detects whether a page is an Article, Product, FAQPage, or Organization and emits the right shape - including required fields most sites silently miss.

JSON-LD (JavaScript Object Notation for Linked Data) is a method of encoding linked data using JSON, combined with Schema.org vocabulary to create structured data that search engines and AI systems can understand. Enables rich search results and knowledge graph inclusion.

## At a glance

- File: `schema.json`
- First released: 2014
- Created by: Schema.org / W3C
- Specification: https://json-ld.org
- Read by: Google Search, Bing, Voice assistants, AI citation systems, Knowledge graph systems

## Why it matters for AI

JSON-LD lets you embed a machine-readable graph of typed entities (Article, Product, Person, Organization, FAQ, Event) inside a single `<script type="application/ld+json">` tag. Search engines and LLM-powered answer engines lift this directly to populate rich results, knowledge panels, and answer citations - it's the format Google explicitly recommends over Microdata or RDFa.

## Example

```
{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "Geordy",
  "applicationCategory": "BusinessApplication",
  "description": "AI optimization platform for generative search engines"
}
```

## Benefits

- Modern standard recommended by Google
- Enables rich search results and knowledge graph inclusion
- Single source of truth for entity data
- Parsed natively by every major search and AI engine

## Best practices

- Use `@context: "https://schema.org"` and pick the most specific type (e.g. `TechArticle`, not just `Article`).
- Mark up only content that is actually visible to users on the page - Google penalizes hidden or contradictory schema.
- Cross-link entities with `@id` URIs so Person -> worksFor -> Organization forms a real graph instead of disconnected blobs.
- Validate every page with both Google's Rich Results Test and Schema.org's validator before shipping.

## Pitfalls

- Stuffing schema with data not present on the page (e.g. fake reviews, ratings) - triggers manual actions.
- Using deprecated or made-up properties; if it isn't on schema.org or pending.schema.org it won't be parsed.
- Multiple conflicting JSON-LD blocks on one page (e.g. two Organization nodes with different logos) confuse parsers.

## Use cases

- **Rich search results**
- **Knowledge graph entity definition**
- **AI citation grounding**

## Adopters

- The New York Times (https://www.nytimes.com)
- Stack Overflow (https://stackoverflow.com)
- Amazon (https://www.amazon.com)
- BBC News (https://www.bbc.com/news)
- IMDb (https://www.imdb.com)
---

Source: https://geordy.ai/formats/schema-json
This is a machine-readable markdown version of that page, generated by Geordy.