Agent skill

GEO Schema Auditor

by zubair-trabzada in zubair-trabzada/geo-seo-claude

Audits a page's Schema.org structured data for AI discoverability, validates it, generates JSON-LD to fill gaps and writes a GEO-SCHEMA-REPORT.md.

MITAuto-check: notesMarketing & SEO

Install GEO Schema Auditor

skills CLI
$ npx skills add zubair-trabzada/geo-seo-claude --skill geo-schema -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install zubair-trabzada/geo-seo-claude geo-schema --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/zubair-trabzada/geo-seo-claude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/geo-schema .claude/skills/geo-schema && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
geo-schema
GitHub stars
11k
Used in
2 other repos
Token cost
~3.7k tokens
SKILL.md length
1,508 words
Files
1
Skills in repo
16
Repo updated
First seen
Licence
MIT

At a glance

Audits a page's Schema.org structured data for AI discoverability, validates it, generates JSON-LD to fill gaps and writes a GEO-SCHEMA-REPORT.md.

  • Works in 6 steps: Detection → Validation → Schema Types for GEO → …
  • Checking what structured data a page already exposes
  • SKILL.md covers Purpose, How to Use This Skill, Step 1: Detection and Step 2: Validation, plus 6 more sections
  • Calls python3; reaches schema.org and wikidata.org

What it does

The skill starts by fetching the target page with the fetch_page.py script from the parent geo skill, because WebFetch drops head content and with it the JSON-LD blocks. It then detects JSON-LD, Microdata and RDFa, treating JSON-LD as the preferred format and flagging a migration when a site only uses the other two. The premise is that structured data tells AI systems what an entity is and how it connects to others.

Each detected block is validated for syntactically valid JSON, a recognized Schema.org type and required properties. The agent then lists missing recommended schemas for the business type, produces ready-to-paste JSON-LD code blocks and saves the findings in GEO-SCHEMA-REPORT.md. The excerpt is truncated, so the per-type requirements are not described here.

When your agent uses it

  • Checking what structured data a page already exposes
  • Fixing invalid or incomplete JSON-LD markup
  • Generating missing JSON-LD suited to a particular business type
  • Replacing Microdata or RDFa with JSON-LD

Example prompts

  • “Audit the structured data on https://example.com/pricing and write the report.”
  • “Validate the JSON-LD blocks on our homepage and list the missing recommended schemas.”
  • “Generate JSON-LD for the contact page of our dental clinic.”

Requirements

  • Python 3 to run the geo skill's fetch_page.py script
  • Network access to fetch the target page
  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash, WebFetch, Write

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Detection
  2. Validation
  3. Schema Types for GEO
  4. Deprecated/Changed Schemas to Flag
  5. sameAs Strategy (CRITICAL for Entity Recognition)
  6. JSON-LD Generation

What it can do on your machine

Read from SKILL.md and the folder at commit 989cae0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Bash
    • WebFetch
    • Write

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • schema.org
    • wikidata.org
    • linkedin.com
    • en.wikipedia.org
    • youtube.com
    • twitter.com
    • github.com
    • crunchbase.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

GEO Schema Auditor loads about 3.7k tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 1,508 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~35
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Grep, Glob, Bash, WebFetch, Write

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from zubair-trabzada/geo-seo-claude at commit 989cae0, republished under its MIT licence (© zubair-trabzada). 1,508 words, ~3,671 tokens.

Download SKILL.mdSave it as .claude/skills/geo-schema/SKILL.md (or your agent's skills folder).
name
geo-schema
description
Schema.org structured data audit and generation optimized for AI discoverability — detect, validate, and generate JSON-LD markup
allowed-tools
Read, Grep, Glob, Bash, WebFetch, Write
version
1.0.0
author
geo-seo-claude
tags
geo, schema, structured-data, json-ld, entity-recognition, ai-discoverability

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:

bash
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

Structure:

json
{
  "@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.

json
{
  "@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.


Show full SKILL.md (602 more words)Show less

Step 4: Deprecated/Changed Schemas to Flag

SchemaStatusNote
HowToRich results deprecated Aug 2023Still useful for AI parsing, but do not promise rich results
FAQPageRestricted to govt/health Aug 2023Still useful for AI parsing (see above)
SpecialAnnouncementDeprecated 2023Was for COVID; remove if still present
CourseInfoReplaced by Course updates 2024Use updated Course schema properties
VideoObject contentUrlChanged behavior 2024Must point to actual video file, not page URL
Review snippetStricter enforcement 2024Self-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.

  1. Wikipedia article — highest authority entity link
  2. Wikidata item — machine-readable entity identifier (e.g., https://www.wikidata.org/wiki/Q12345)
  3. LinkedIn — company page or personal profile
  4. YouTube — channel URL
  5. Twitter/X — profile URL
  6. Facebook — page URL
  7. Crunchbase — company profile (for startups/tech)
  8. GitHub — organization or personal profile (for tech)
  9. Google Scholar — author profile (for researchers/academics)
  10. ORCID — researcher identifier (for academics)
  11. Instagram — profile URL
  12. Apple App Store / Google Play — app listings (for software)
  13. BBB — Better Business Bureau listing (for US businesses)
  14. Industry directories — relevant vertical directories
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
json
{
  "@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)

CriterionPointsHow to Score
Organization/Person schema present and complete1515 if full, 10 if basic, 0 if none
sameAs links (5+ platforms)153 per valid sameAs link, max 15
Article schema with author details1010 if full author schema, 5 if name only, 0 if none
Business-type-specific schema present1010 if complete, 5 if partial, 0 if missing
WebSite + SearchAction55 if present, 0 if not
BreadcrumbList on inner pages55 if present, 0 if not
JSON-LD format (not Microdata/RDFa)55 if JSON-LD, 3 if mixed, 0 if only Microdata/RDFa
Server-rendered (not JS-injected)1010 if in HTML source, 5 if JS but in head, 0 if dynamic JS
speakable property on articles55 if present, 0 if not
Valid JSON + valid Schema.org types1010 if no errors, 5 if minor issues, 0 if major errors
knowsAbout property on Organization/Person55 if present with 3+ topics, 0 if missing
No deprecated schemas present55 if clean, 0 if deprecated schemas found

Output Format

Generate GEO-SCHEMA-REPORT.md with:

markdown
# 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

© zubair-trabzada, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/geo-schema of zubair-trabzada/geo-seo-claude.

Open the folder on GitHubat commit 989cae0

Used in 2 other repositories

We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in zubair-trabzada/geo-seo-claude, which our catalogue first saw on October 7, 2026.

Compare with similar skills

GEO Schema Auditor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

GEO Schema Auditor compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
GEO Schema Auditor this skillzubair-trabzada/geo-seo-claude11k2 repos~3.7kAutomated safety check: NotesMIT
Universal SEO AnalysisAgriciDaniel/claude-seo19k—~4.9kAutomated safety check: PassMIT
SEO and GEO Auditdageno-agents/seo-geo-audit176—~2kAutomated safety check: PassMIT
Openpost SEOgetopenpost/openpost663—~766Automated safety check: PassAGPL-3.0
Full Website SEO AuditAgriciDaniel/claude-seo19k—~2.6kAutomated safety check: PassMIT
Generative Engine Optimizationtech-leads-club/agent-skills7k—~2.5kAutomated safety check: PassMIT

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Works with

Categories

Questions about GEO Schema Auditor

What does GEO Schema Auditor do?

Audits a page's Schema.org structured data for AI discoverability, validates it, generates JSON-LD to fill gaps and writes a GEO-SCHEMA-REPORT.md. py script from the parent geo skill, because WebFetch drops head content and with it the JSON-LD blocks. It then detects JSON-LD, Microdata and RDFa, treating JSON-LD as the preferred format and flagging a migration when a site only uses the other two.

When should I use GEO Schema Auditor?

GEO Schema Auditor fits situations like: checking what structured data a page already exposes; fixing invalid or incomplete JSON-LD markup; generating missing JSON-LD suited to a particular business type; replacing Microdata or RDFa with JSON-LD.

How do I install GEO Schema Auditor in Claude Code?

Run `npx skills add zubair-trabzada/geo-seo-claude --skill geo-schema -a claude-code`. Or copy the skill folder (skills/geo-schema in zubair-trabzada/geo-seo-claude) into .claude/skills/geo-schema in your project. Claude Code loads it when a task matches its description.

How do I install GEO Schema Auditor in Codex?

Run `npx skills add zubair-trabzada/geo-seo-claude --skill geo-schema -a codex`. Or copy the skill folder (skills/geo-schema in zubair-trabzada/geo-seo-claude) into .agents/skills/geo-schema in your project. Codex loads it when a task matches its description.

Can I use GEO Schema Auditor in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zubair-trabzada/geo-seo-claude --skill geo-schema -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/geo-schema, .gemini/skills/geo-schema, .github/skills/geo-schema and .opencode/skills/geo-schema in your project.

What does GEO Schema Auditor need to run?

Going by SKILL.md and its folder, GEO Schema Auditor needs the command-line tools its instructions call (python3). Our summary lists: Python 3 to run the geo skill's fetch_page.py script; Network access to fetch the target page. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash, WebFetch, Write.

Does GEO Schema Auditor access the network?

SKILL.md names 8 domains. In commands or code: schema.org, wikidata.org, linkedin.com, en.wikipedia.org, youtube.com, twitter.com, github.com and crunchbase.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is GEO Schema Auditor safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does GEO Schema Auditor use?

GEO Schema Auditor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does GEO Schema Auditor use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to GEO Schema Auditor?

Skills that share tags, products or a category with GEO Schema Auditor: Universal SEO Analysis (AgriciDaniel/claude-seo, 19k stars), SEO and GEO Audit (dageno-agents/seo-geo-audit, 176 stars), Openpost SEO (getopenpost/openpost, 663 stars) and Full Website SEO Audit (AgriciDaniel/claude-seo, 19k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains GEO Schema Auditor?

zubair-trabzada (a GitHub user) maintains it in zubair-trabzada/geo-seo-claude, which has 10,982 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on October 10, 2026.

Source: zubair-trabzada/geo-seo-claude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.