Fill in your article details to generate optimized JSON-LD schema
Comma-separated keywords for your article
First entity becomes "about", rest become "mentions"
Copy and paste this JSON-LD into your HTML <head> section
AI SEO focuses on entities rather than keywords. By explicitly defining 'about' and 'mentions' in your schema, you provide a knowledge graph that LLMs can digest instantly, increasing your chances of being cited in AI-generated answers.
Learn how to optimize your content for the next generation of search engines and AI models
AI SEO is the practice of optimizing content to be easily discoverable and understandable by Large Language Models (LLMs). Unlike traditional crawlers, LLMs value semantic connections and entity relationships.
JSON-LD is the preferred format for Google and AI agents. It provides a clean, machine-readable map of your article's intent, author authority, and core topics.
Explicitly linking your content to known entities (like 'Artificial Intelligence' or specific brands) helps search engines place your content accurately within the global knowledge graph.
Follow these simple steps to generate and implement AI-optimized schema markup
Enter your article's headline, description, author information, and publication dates. The headline is required, while other fields enhance the schema's richness.
List the main topics and concepts your article covers. The first entity becomes the primary "about" topic, while others are listed as "mentions" for comprehensive semantic coverage.
Click the copy button and paste the generated JSON-LD script into the <head> section of your HTML. The schema will be automatically recognized by search engines and AI models.
JSON-LD (JavaScript Object Notation for Linked Data) is a method of encoding structured data using JSON. It's the recommended format by Google for implementing schema markup because it's easy to read, write, and doesn't interfere with your HTML content. Search engines and AI models use this data to better understand your content's context and meaning.
AI models rely on structured data to understand content semantics. By providing explicit "about" and "mentions" entities, you're creating a knowledge graph that LLMs can easily parse. This increases the likelihood of your content being cited in AI-generated responses and featured in AI-powered search results.
The JSON-LD script should be placed within the <head> section of your HTML document, preferably before the closing </head> tag. You can also place it at the end of the <body> section, but the <head> placement is recommended for better crawlability.
The "about" property indicates the primary topic or subject of your article - what it's fundamentally about. The "mentions" property lists other entities that are discussed or referenced in the content but aren't the main focus. This tool automatically assigns the first entity you enter as "about" and the rest as "mentions".
Yes! This AI SEO Schema Generator is completely free and open-source. We built it to help content creators and SEO professionals transition to the AI-first search era. Your data is saved locally in your browser and never sent to any server.
Currently, this tool generates TechArticle schema, which is ideal for technical articles, tutorials, and how-to guides. However, the same principles apply to other article types. You can manually adjust the "@type" field in the generated JSON-LD to "Article", "BlogPosting", "NewsArticle", or other schema.org types as needed.
Use Google's Rich Results Test or Schema.org Validator to test your implementation. These tools will show you if your schema is valid and how search engines will interpret it.
All your input data is stored locally in your browser using localStorage. Nothing is sent to any server. This means your data persists across page reloads, but only on the device and browser you're using. Clear your browser data or use the "Clear Data" button to remove saved information.
Complete guide to understanding and implementing AI-optimized schema markup
@context: Defines the vocabulary being used (always "https://schema.org" for schema markup)
@type: Specifies the type of content (TechArticle, Article, BlogPosting, etc.)
headline: The title of your article (required)
description: A brief summary of the article content
author: Information about the content creator (Person type)
publisher: The organization publishing the content
datePublished: When the article was first published (ISO 8601 format)
dateModified: When the article was last updated
about: The primary subject/topic of the article
mentions: Additional entities referenced in the content
keywords: Comma-separated keywords describing the content
Here's how to implement the generated schema in your HTML:
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Your Article Title</title>
<!-- Generated JSON-LD Schema -->
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "TechArticle",
"headline": "Your Article Title",
...
}
</script>
</head>
<body>
<!-- Your content here -->
</body>
</html>
✓ Be Specific: Use precise entity names that match recognized knowledge graph entries
✓ Stay Relevant: Only include entities that are actually discussed in your content
✓ Update Regularly: Keep dateModified current when you update content
✓ Author Authority: Include author URLs to establish expertise and authority
✓ Quality Images: Use high-quality, relevant images with proper URLs
✓ Validate: Always test your schema with Google's Rich Results Test
✗ Missing Required Fields: Always include at least headline, author, and publisher
✗ Incorrect Date Format: Use ISO 8601 format (YYYY-MM-DD)
✗ Duplicate Schema: Don't add multiple identical schemas to the same page
✗ Mismatched Content: Ensure schema data matches actual page content
✗ Broken URLs: Verify all image and profile URLs are accessible