ClawHub

Schema Markup Generator

Generate complete, validated Schema.org JSON-LD markup for any content type to boost AI citation rates. Creates structured data for Organization, FAQPage, Article, BlogPosting, Product, HowTo, BreadcrumbList, WebSite, VideoObject, and ImageObject schemas. Use whenever the user mentions adding schema markup, generating structured data, creating JSON-LD, implementing Schema.org, optimizing for rich snippets, or wants to improve how AI understands and cites their content. Also trigger for requests about Organization schema, FAQ schema, Article markup, Product schema, or any structured data implementation.

Audits

Pass
ClawScanPass

Agentic behavior and permission review.

Static analysisPass

Pattern checks against bundled files.

VirusTotalPass

Multi-engine malware detections and file reputation.

Install

openclaw skills install geo-schema-gen

Schema Markup Generator

Methodology by GEOly AI (geoly.ai) — structured data is the language AI uses to understand your brand.

Generate production-ready Schema.org JSON-LD markup for any page type.

Quick Start

Generate schema for your page:

python scripts/generate_schema.py --type <schema-type> [--url <page-url>]

Example:

python scripts/generate_schema.py --type Organization --url example.com
python scripts/generate_schema.py --type FAQPage --file faqs.json

Why Schema Matters for GEO

Structured data helps AI platforms understand:

  • What your content is (entity type)
  • Who created it (author, publisher)
  • When it was published (freshness)
  • How it relates to other content (breadcrumbs)

Without schema, AI systems rely on NLP inference which is less reliable.

Supported Schema Types

TypePriorityBest For
Organization🔴 CriticalHomepage, About page — establishes brand entity
FAQPage🔴 CriticalFAQ/Support pages — feeds AI Q&A answers
Article / BlogPosting🟡 HighBlog posts, news — improves citability
Product🟡 HighProduct/pricing pages — enables shopping citations
HowTo🟡 HighTutorials, guides — feeds step-by-step answers
WebSite🟡 HighHomepage — enables site search in AI
BreadcrumbList🔵 MediumAll pages — improves navigation understanding
VideoObject🔵 MediumVideo pages — enables video citations
ImageObject🔵 MediumImage galleries — enables image citations
LocalBusiness🔵 MediumPhysical locations — local AI search

Full schema reference: See references/schema-types.md

Generation Methods

Method 1: Interactive (Recommended)

python scripts/generate_schema.py --type Organization --interactive

Guided prompts for all required and optional fields.

Method 2: From URL (Auto-Extract)

python scripts/generate_schema.py --type Article --url https://example.com/blog/post

Automatically extracts metadata from the page.

Method 3: From JSON Input

python scripts/generate_schema.py --type FAQPage --file faqs.json

Where faqs.json contains your content data.

Method 4: Batch Generate

python scripts/batch_generate.py sitemap.xml --output schemas/

Generate schemas for all pages in a sitemap.

Validation

Validate generated schema:

python scripts/validate_schema.py schema.json

Checks for:

  • Required fields present
  • Valid Schema.org types
  • Proper JSON-LD syntax
  • Google Rich Results eligibility

Implementation

Add to Your Page

Paste the generated JSON-LD inside your HTML <head>:

<head>
  <script type="application/ld+json">
  {
    "@context": "https://schema.org",
    "@type": "Organization",
    ...
  }
  </script>
</head>

Test Before Deploying

  1. Schema.org Validator: https://validator.schema.org
  2. Google Rich Results Test: https://search.google.com/test/rich-results
  3. JSON-LD Playground: https://json-ld.org/playground/

Common Mistakes

❌ Wrong: Multiple conflicting Organization schemas on same page ✅ Right: One comprehensive Organization schema

❌ Wrong: Using http://schema.org (insecure) ✅ Right: Using https://schema.org (secure)

❌ Wrong: Copy-pasting without updating placeholder values ✅ Right: All fields contain actual, accurate data

Advanced Usage

Multiple Schemas per Page

Some pages need multiple schema types. Combine them in an array:

python scripts/generate_schema.py --types Organization,WebSite --url example.com

Nested Entities

Generate related schemas together:

python scripts/generate_schema.py --type Product \
  --with-offer --with-review --with-brand

Custom Properties

Add custom properties not in the generator:

python scripts/generate_schema.py --type Organization \
  --custom '{"knowsAbout": ["SEO", "AI", "Machine Learning"]}'

Output Formats

  • JSON-LD (default): Ready to paste into HTML
  • JSON: Raw structured data
  • HTML: Complete <script> tag
  • Markdown: With explanations

Schema Hierarchy

Understanding how schemas relate:

Organization (top-level entity)
├── WebSite (belongs to Organization)
├── Product (offered by Organization)
│   ├── Offer (pricing for Product)
│   └── Review (of Product)
├── Article (published by Organization)
│   ├── Author (Person or Organization)
│   └── Publisher (Organization)
└── LocalBusiness (subtype of Organization)
    └── Place (physical location)

See Also