Geo Schema

Name: Geo Schema
Author: zubair-trabzada

zubair-trabzada/geo-seo-claude

484 installs
9.2k repo stars
Updated August 4, 2026
zubair-trabzada/geo-seo-claude

geo-schema is an agent skill (version 1.0.0) that detects, validates, and generates Schema.org JSON-LD structured data for developers who need AI discoverability and GEO optimization on any website.

About

geo-schema is version 1.0.0 of a GEO-focused structured data skill from zubair-trabzada/geo-seo-claude. It detects and validates JSON-LD, Microdata, and RDFa markup on any site, identifies missing schemas by business type, generates ready-to-use JSON-LD code, and reports GEO optimization findings. Structured data serves as the machine-readable signal telling AI systems what an entity is and how it connects to other entities—a role distinct from traditional Google rich results. Allowed tools include Read, Grep, Glob, Bash, WebFetch, and Write for full audit-to-implementation workflows. Tags cover geo, schema, structured-data, json-ld, entity-recognition, and ai-discoverability. Developers reach for geo-schema when launching sites that need AI citation readiness, auditing existing markup gaps, or generating business-type-specific Schema.org templates.

Detects existing JSON-LD, Microdata, and RDFa structured data
Validates against Schema.org specifications
Generates ready-to-use JSON-LD code blocks
Outputs GEO-SCHEMA-REPORT.md with findings
Improves citation probability across AI search platforms

Geo Schema by the numbers

484 all-time installs (skills.sh)
Ranked #781 of 1,879 Marketing & SEO skills by installs in the Skillselion catalog
Data as of Aug 5, 2026 (Skillselion catalog sync)

npx skills add https://github.com/zubair-trabzada/geo-seo-claude --skill geo-schema

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Installs	484
repo stars	★ 9.2k
Last updated	August 4, 2026
Repository	zubair-trabzada/geo-seo-claude ↗

How do you audit JSON-LD for AI discoverability?

Detects and validates structured data (JSON-LD, Microdata, RDFa) on any site, identifies missing schemas by business type, generates ready-to-use JSON-LD code, and reports GEO optimization findings.

Who is it for?

Developers and SEO engineers launching or auditing websites who need Schema.org JSON-LD validated for AI discoverability and generative search citations.

Skip if: Native mobile apps without web pages or teams satisfied with basic Google rich-result markup unrelated to AI entity recognition.

When should I use this skill?

The developer asks to audit structured data, generate JSON-LD schemas, check Schema.org markup gaps, or optimize a site for AI discoverability and GEO.

What you get

Structured data audit report, missing schema identification, ready-to-use JSON-LD snippets, and GEO optimization findings

Structured data audit report
JSON-LD code snippets
GEO optimization findings

By the numbers

Skill version 1.0.0
Supports 3 markup formats: JSON-LD, Microdata, and RDFa
Allowed tools: Read, Grep, Glob, Bash, WebFetch, Write

Files

SKILL.mdMarkdownGitHub ↗

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
review: Array of Review schemas
hasMap: URL to Google Maps

Article + Author (CRITICAL for publishers)

The Author schema is one of the strongest E-E-A-T signals for AI platforms.

Article required:

@type: "Article" (or NewsArticle, BlogPosting, TechArticle)
headline: Article title
datePublished: ISO 8601
dateModified: ISO 8601 (critical for freshness signals)
author: Person or Organization schema
publisher: Organization schema with logo
image: Representative image

Author (Person) required for GEO:

name: Full name
url: Author page URL on the site
sameAs: LinkedIn, Twitter, personal site, Google Scholar, ORCID
jobTitle: Professional title
worksFor: Organization schema
knowsAbout: Array of expertise areas
alumniOf: Educational institutions
award: Professional awards

Product (for e-commerce)

Required:

name, description, image
offers: Offer with price, priceCurrency, availability
brand: Brand schema
sku or gtin/mpn

Recommended for GEO:

aggregateRating: AggregateRating
review: Array of individual reviews
category: Product category
material, weight, width, height (where applicable)

FAQPage

Status as of 2024: Google restricts FAQ rich results to government and health sites. However, the FAQPage schema still serves GEO purposes — AI platforms parse FAQ structured data for question-answer extraction. Implement it for AI readability even though rich results may not appear.

Structure:

@type: "FAQPage"
mainEntity: Array of Question schemas, each with acceptedAnswer containing an Answer schema

SoftwareApplication (for SaaS)

Required:

name, description
applicationCategory: e.g., "BusinessApplication"
operatingSystem: Supported platforms
offers: Pricing

Recommended for GEO:

aggregateRating: User ratings
featureList: Array of features (strong citation signal)
screenshot: Screenshots
softwareVersion: Current version
releaseNotes: Link to changelog

WebSite + SearchAction (for sitelinks search box)

Structure:

{
  "@type": "WebSite",
  "name": "Site Name",
  "url": "https://example.com",
  "potentialAction": {
    "@type": "SearchAction",
    "target": {
      "@type": "EntryPoint",
      "urlTemplate": "https://example.com/search?q={search_term_string}"
    },
    "query-input": "required name=search_term_string"
  }
}

Person (standalone — for personal brands, authors, thought leaders)

Use as a standalone schema on About/Bio pages. This builds the entity graph for individual expertise.

Required: name, url Recommended for GEO: sameAs, jobTitle, worksFor, knowsAbout, alumniOf, award, description, image

speakable Property (for voice/AI assistants)

The speakable property marks specific sections of content as particularly suitable for voice and AI assistant consumption. Add to Article or WebPage schemas.

{
  "@type": "Article",
  "speakable": {
    "@type": "SpeakableSpecification",
    "cssSelector": [".article-summary", ".key-takeaway"]
  }
}

This signals to AI assistants which passages are the best candidates for citation or reading aloud.

---

Step 4: Deprecated/Changed Schemas to Flag

Schema	Status	Note
HowTo	Rich results deprecated Aug 2023	Still useful for AI parsing, but do not promise rich results
FAQPage	Restricted to govt/health Aug 2023	Still useful for AI parsing (see above)
SpecialAnnouncement	Deprecated 2023	Was for COVID; remove if still present
CourseInfo	Replaced by Course updates 2024	Use updated Course schema properties
VideoObject `contentUrl`	Changed behavior 2024	Must point to actual video file, not page URL
Review snippet	Stricter enforcement 2024	Self-serving reviews on product pages may not display

Flag any deprecated schemas found and recommend replacements.

---

Step 5: sameAs Strategy (CRITICAL for Entity Recognition)

The sameAs property is the single most important structured data property for GEO. It tells AI systems: "This entity on my website is the SAME entity as these profiles elsewhere." This creates the entity graph that AI platforms use to verify, trust, and cite sources.

sameAs Audit Process

1. Collect all known web presences for the entity 2. Check that each URL resolves (not 404 or redirected) 3. Verify the Organization/Person schema includes ALL of them 4. Check that the information on each platform is consistent (name, description, founding date, etc.) 5. Flag any platforms where the entity should have a presence but does not

---

Step 6: JSON-LD Generation

Based on the detected business type, generate ready-to-paste JSON-LD blocks. Always generate:

1. Organization or Person (depending on entity type) — always 2. WebSite with SearchAction — always for the homepage 3. Business-type-specific — Article for publishers, Product for e-commerce, LocalBusiness for local, SoftwareApplication for SaaS 4. BreadcrumbList — for any page deeper than homepage

Generation Rules

Use the @graph pattern to include multiple schemas in one JSON-LD block
All URLs must be absolute (not relative)
Include @id properties for cross-referencing between schemas
Use ISO 8601 for all dates
Include speakable on Article schemas with CSS selectors pointing to key content sections
Place JSON-LD in <head> section — NOT injected via JavaScript

Template: Organization with Full GEO Signals

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://example.com/#organization",
  "name": "Company Name",
  "url": "https://example.com",
  "logo": {
    "@type": "ImageObject",
    "url": "https://example.com/logo.png",
    "width": 600,
    "height": 60
  },
  "description": "Concise description of what the company does.",
  "foundingDate": "2020-01-15",
  "founder": {
    "@type": "Person",
    "name": "Founder Name",
    "sameAs": "https://www.linkedin.com/in/founder"
  },
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "123 Main St",
    "addressLocality": "City",
    "addressRegion": "State",
    "postalCode": "12345",
    "addressCountry": "US"
  },
  "contactPoint": {
    "@type": "ContactPoint",
    "telephone": "+1-555-555-5555",
    "contactType": "customer service",
    "email": "support@example.com"
  },
  "sameAs": [
    "https://en.wikipedia.org/wiki/Company_Name",
    "https://www.wikidata.org/wiki/Q12345",
    "https://www.linkedin.com/company/company-name",
    "https://www.youtube.com/@companyname",
    "https://twitter.com/companyname",
    "https://github.com/companyname",
    "https://www.crunchbase.com/organization/company-name"
  ],
  "knowsAbout": [
    "Topic 1",
    "Topic 2",
    "Topic 3"
  ]
}

---

Scoring Rubric (0-100)

Criterion	Points	How to Score
Organization/Person schema present and complete	15	15 if full, 10 if basic, 0 if none
sameAs links (5+ platforms)	15	3 per valid sameAs link, max 15
Article schema with author details	10	10 if full author schema, 5 if name only, 0 if none
Business-type-specific schema present	10	10 if complete, 5 if partial, 0 if missing
WebSite + SearchAction	5	5 if present, 0 if not
BreadcrumbList on inner pages	5	5 if present, 0 if not
JSON-LD format (not Microdata/RDFa)	5	5 if JSON-LD, 3 if mixed, 0 if only Microdata/RDFa
Server-rendered (not JS-injected)	10	10 if in HTML source, 5 if JS but in head, 0 if dynamic JS
speakable property on articles	5	5 if present, 0 if not
Valid JSON + valid Schema.org types	10	10 if no errors, 5 if minor issues, 0 if major errors
knowsAbout property on Organization/Person	5	5 if present with 3+ topics, 0 if missing
No deprecated schemas present	5	5 if clean, 0 if deprecated schemas found

---

Output Format

Generate GEO-SCHEMA-REPORT.md with:

# GEO Schema & Structured Data Report — [Domain]
Date: [Date]

## Schema Score: XX/100

## Detected Schemas
| Page | Schema Type | Format | Status | Issues |
|---|---|---|---|---|
| / | Organization | JSON-LD | Valid | Missing sameAs |
| /blog/post-1 | Article | JSON-LD | Valid | No author schema |

## Validation Results
[List each schema with pass/fail per property]

## Missing Recommended Schemas
[List schemas that should be present based on business type but are not]

## sameAs Audit
| Platform | URL | Status |
|---|---|---|
| Wikipedia | [URL or "Not found"] | Present/Missing |
| LinkedIn | [URL or "Not found"] | Present/Missing |
[Continue for all recommended platforms]

## Generated JSON-LD Code
[Ready-to-paste JSON-LD blocks for each missing or incomplete schema]

## Implementation Notes
- Where to place each JSON-LD block
- Server-rendering requirements
- Testing with Google Rich Results Test and Schema.org Validator

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How it compares

Pick geo-schema over generic SEO skills when the goal is AI entity recognition and GEO citation readiness, not only Google rich snippets.

FAQ

What markup formats does geo-schema support?

geo-schema detects and validates JSON-LD, Microdata, and RDFa on any site. It identifies missing Schema.org types by business category and generates ready-to-use JSON-LD code optimized for AI discoverability beyond traditional rich results.

How is geo-schema different from standard SEO schema tools?

geo-schema focuses on generative engine optimization where structured data tells AI models what an entity is and how it connects to others. Version 1.0.0 reports GEO findings for AI citation readiness, not only Google rich-result eligibility.

Marketing & SEOseocontentdistribution

About

Geo Schema by the numbers

Add your badge

How do you audit JSON-LD for AI discoverability?

Who is it for?

When should I use this skill?

What you get

By the numbers

Files

GEO Schema & Structured Data

Purpose

How to Use This Skill

Step 1: Detection

Scan for JSON-LD

Scan for Microdata

Scan for RDFa

Priority Order

Step 2: Validation

Step 3: Schema Types for GEO

Organization (CRITICAL — every business site)

LocalBusiness (for businesses with physical locations)

Article + Author (CRITICAL for publishers)

Product (for e-commerce)

FAQPage

SoftwareApplication (for SaaS)

WebSite + SearchAction (for sitelinks search box)

Person (standalone — for personal brands, authors, thought leaders)

speakable Property (for voice/AI assistants)

Step 4: Deprecated/Changed Schemas to Flag

Step 5: sameAs Strategy (CRITICAL for Entity Recognition)

Recommended sameAs Links (in priority order)

sameAs Audit Process

Step 6: JSON-LD Generation

Generation Rules

Template: Organization with Full GEO Signals

Scoring Rubric (0-100)

Output Format

Related skills

How it compares

FAQ

What markup formats does geo-schema support?

How is geo-schema different from standard SEO schema tools?

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