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SEO48k · #3112

geo-schema

Enables your agent to analyze and generate Schema.org structured data. This helps search engines and AI better understand your content, improving online visibility.

What it does

This tool helps audit and create structured data for your website. This data acts like a map, enabling AI systems to understand what your business does, where it's located, and how it connects to other information.

When to use it

  • ✓When you launch a new website or page.
  • ✓When updating important business information.
  • ✓To improve how search engines and AIs understand your business.

Example of what to ask your AI

“Audit the structured data for the page [URL] and generate a report.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/geo-schema/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/geo-schema/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool first fetches the page content and looks for special markings (structured data). It then checks if these markings are correct, suggests improvements, or creates new markings in a format that AIs understand best.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill geo-schema

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/geo-schema/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

GEO Schema & Structured Data

Purpose

Structured data is the primary machine-readable signal that tells AI systems what an entity IS, what it does, and how it connects to other entities. While schema markup has traditionally been about earning Google rich results, its role in GEO is fundamentally different: structured data is how AI models understand and trust your entity. A complete entity graph in structured data dramatically increases citation probability across all AI search platforms.

How to Use This Skill

  1. Fetch the target page HTML using fetch_page.py (see note below)
  2. Detect all existing structured data (JSON-LD, Microdata, RDFa)
  3. Validate detected schemas against Schema.org specifications
  4. Identify missing recommended schemas based on business type
  5. Generate ready-to-use JSON-LD code blocks
  6. Output GEO-SCHEMA-REPORT.md

Step 1: Detection

IMPORTANT: WebFetch converts HTML to markdown and strips <head> content, which removes JSON-LD blocks. Use fetch_page.py instead:

python3 ~/.claude/skills/geo/scripts/fetch_page.py <url> page

The output includes a structured_data array with all parsed JSON-LD blocks from the page.

Scan for JSON-LD

Look for <script type="application/ld+json"> blocks in the HTML. Parse each block as JSON. A page may contain multiple JSON-LD blocks — collect all of them.

Scan for Microdata

Look for elements with itemscope, itemtype, and itemprop attributes. Map the hierarchy of nested items. Note: Microdata is harder for AI crawlers to parse than JSON-LD. Flag a recommendation to migrate to JSON-LD if Microdata is the only format found.

Scan for RDFa

Look for elements with typeof, property, and vocab attributes. Similar to Microdata — recommend migration to JSON-LD.

Priority Order

JSON-LD is the strongly recommended format for GEO. Google, Bing, and AI platforms all process JSON-LD most reliably. If the site uses Microdata or RDFa exclusively, flag this as a high-priority migration.


Step 2: Validation

For each detected schema block, validate:

  1. Valid JSON: Is the JSON-LD syntactically valid? Check for trailing commas, unquoted keys, malformed strings.
  2. Valid @type: Does the @type match a recognized Schema.org type? Check against https://schema.org/docs/full.html.
  3. Required Properties: Does the schema include all required properties for its type? (See per-type requirements below.)
  4. Recommended Properties: Does the schema include recommended properties that increase AI discoverability?
  5. sameAs Links: Does the schema include sameAs properties linking to other platform presences?
  6. URL Validity: Do all URLs in the schema resolve (not 404)?
  7. Nesting: Is the schema properly nested (e.g., author inside Article, address inside Organization)?
  8. Rendering Method: Is the JSON-LD in the server-rendered HTML or injected via JavaScript? Per Google's December 2025 guidance, JavaScript-injected structured data may face delayed processing. Flag any schema that requires JS execution.

Step 3: Schema Types for GEO

Organization (CRITICAL — every business site)

Essential for entity recognition across all AI platforms. This is how AI models identify WHAT the business is.

Required properties:

  • @type: "Organization" (or subtype: Corporation, LocalBusiness, etc.)
  • name: Official business name
  • url: Official website URL
  • logo: URL to logo image (ImageObject preferred)

Recommended properties for GEO:

  • sameAs: Array of ALL platform URLs (see sameAs strategy below)
  • description: 1-2 sentence description of the organization
  • foundingDate: ISO 8601 date
  • founder: Person schema
  • address: PostalAddress schema
  • contactPoint: ContactPoint with telephone, email, contactType
  • areaServed: Geographic area
  • numberOfEmployees: QuantitativeValue
  • industry: Text or DefinedTerm
  • award: Array of awards received
  • knowsAbout: Array of topics the organization is expert in (strong GEO signal)

LocalBusiness (for businesses with physical locations)

Extends Organization. Critical for local AI search results and Google Gemini.

Additional required properties:

  • address: Full PostalAddress
  • telephone: Phone number
  • openingHoursSpecification: Operating hours

Recommended for GEO:

  • geo: GeoCoordinates (latitude, longitude)
  • priceRange: Price indicator
  • aggregateRating: AggregateRating schema

…

FAQ

Why is structured data important for AI?

Structured data is like an instruction manual for AIs. It clearly and organizedly explains who you are, what you offer, and how you relate to the world, increasing the chances of being found and understood.

What is the preferred structured data format?

The JSON-LD format is highly recommended because it's easier for AIs to process and understand compared to other formats like Microdata or RDFa.

Do I need to be a programmer to use this?

No, this tool is designed for use without programming knowledge. It automates the auditing and generation of structured data for you.

Details

Original description by the author

Schema.org structured data audit and generation optimized for AI discoverability — detect, validate, and generate JSON-LD markup

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#3112
License
MIT
Updated
10/15/2026

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