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Agent skill

Schema Markup

by alirezarezvani in alirezarezvani/claude-skills

When the user wants to implement, audit, or validate structured data (schema markup) on their website.

MITAuto-check passedMarketing & SEO

Install Schema Markup

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill schema-markup -a claude-code

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

GitHub CLI
$ gh skill install alirezarezvani/claude-skills schema-markup --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/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/marketing-skill/skills/schema-markup .claude/skills/schema-markup && 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
schema-markup
GitHub stars
28k
Used in
1 other repo
Token cost
~2.9k tokens
SKILL.md length
1,413 words
Files
4 (incl. scripts, references)
Skills in repo
342
Repo updated
First seen
Licence
MIT

At a glance

When the user wants to implement, audit, or validate structured data (schema markup) on their website.

  • Works in 3 steps: Current State → Site Details → Goals
  • Wants to implement
  • SKILL.md covers Before Starting, How This Skill Works, Schema Type Selection and Implementation Patterns, plus 7 more sections
  • Runs Python scripts from its folder; calls python3; reaches schema.org and search.google.com

What it does

Schema Markup is an agent skill from alirezarezvani/claude-skills. When the user wants to implement, audit, or validate structured data (schema markup) on their website. Use when the user mentions 'structured data,' 'schema.org,' 'JSON-LD,' 'rich results,' 'rich snippets,' 'schema markup,' 'FAQ schema,' 'Product schema,' 'HowTo schema,' or 'structured data errors in Search Console.' Also use when someone asks why their content isn't showing rich results or wants to improve AI search visibility. NOT for general SEO audits (use seo-audit) or technical SEO crawl issues (use…

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/implementation-patterns.md`, `references/schema-types-guide.md` and `scripts/schema_validator.py`).

It sits in Marketing & SEO, covering Schema markup. It works with Google Search Console. The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.

When your agent uses it

  • Wants to implement
  • Validate structured data (schema markup) on their website
  • The user mentions structured data
  • Structured data errors in Search Console. Also use when someone asks why their content isnt showing rich results

Example prompts

  • “structured data,”
  • “schema.org,”
  • “JSON-LD,”
  • “/schema-markup”

Requirements

  • Python 3

Workflow steps

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

  1. Current State
  2. Site Details
  3. Goals

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    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
    • search.google.com
    • validator.schema.org

    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

Schema Markup loads about 2.9k tokens when it runs, and up to ~8k if it reads all its reference files. Until then it costs about 136 tokens; SKILL.md has 1,413 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~136
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~8k

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 passed

The automated check found no risky patterns in SKILL.md.

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); the scripts in this folder are not scanned.

SKILL.md

The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 1,413 words, ~2,898 tokens.

Download SKILL.mdSave it as .claude/skills/schema-markup/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
schema-markup
description
When the user wants to implement, audit, or validate structured data (schema markup) on their website. Use when the user mentions 'structured data,' 'schema.org,' 'JSON-LD,' 'rich results,' 'rich snippets,' 'schema markup,' 'FAQ schema,' 'Product schema,' 'HowTo schema,' or 'structured data errors in Search Console.' Also use when someone asks why their content isn't showing rich results or wants to improve AI search visibility. NOT for general SEO audits (use seo-audit) or technical SEO crawl issues (use site-architecture).
license
MIT
metadata.version
1.0.0
metadata.author
Alireza Rezvani
metadata.category
marketing
metadata.updated
2026-03-06

Schema Markup Implementation

You are an expert in structured data and schema.org markup. Your goal is to help implement, audit, and validate JSON-LD schema that earns rich results in Google, improves click-through rates, and makes content legible to AI search systems.

Before Starting

Check for context first: If .claude/product-marketing-context.md exists, read it before asking questions. Use that context and only ask for what's missing.

Gather this context:

1. Current State
  • Do they have any existing schema markup? (Check source, GSC Coverage report, or run the validator script)
  • Any rich results currently showing in Google?
  • Any structured data errors in Search Console?
2. Site Details
  • CMS platform (WordPress, Webflow, custom, etc.)
  • Page types that need markup (homepage, articles, products, FAQ, local business)
  • Can they edit <head> tags, or do they need a plugin/GTM?
3. Goals
  • Rich results target (FAQ dropdowns, star ratings, breadcrumbs, HowTo steps, etc.)
  • AI search visibility (getting cited in AI Overviews, Perplexity, etc.)
  • Fix existing errors vs implement net new

How This Skill Works

Mode 1: Audit Existing Markup

When they have a site and want to know what schema exists and what's broken.

  1. Run scripts/schema_validator.py on the page HTML (or paste URL for manual check)
  2. Review Google Search Console → Enhancements → check all schema error reports
  3. Cross-reference against references/schema-types-guide.md for required fields
  4. Deliver audit report: what's present, what's broken, what's missing, priority order
Mode 2: Implement New Schema

When they need to add structured data to pages — from scratch or to a new page type.

  1. Identify the page type and the right schema types (see schema selection table below)
  2. Pull the JSON-LD pattern from references/implementation-patterns.md
  3. Populate with real page content
  4. Advise on placement (inline <script> in <head>, CMS plugin, GTM injection)
  5. Deliver complete, copy-paste-ready JSON-LD for each page type
Mode 3: Validate & Fix

When schema exists but rich results aren't showing or GSC reports errors.

  1. Test at rich-results.google.com and validator.schema.org
  2. Map errors to specific missing or malformed fields
  3. Deliver corrected JSON-LD with the broken fields fixed
  4. Explain why the fix works (so they don't repeat the mistake)

Schema Type Selection

Pick the right schema for the page — stacking compatible types is fine, but don't add schema that doesn't match the page content.

Page TypePrimary SchemaSupporting Schema
HomepageOrganizationWebSite (with SearchAction)
Blog post / articleArticleBreadcrumbList, Person (author)
How-to guideHowToArticle, BreadcrumbList
FAQ pageFAQPage—
Product pageProductOffer, AggregateRating, BreadcrumbList
Local businessLocalBusinessOpeningHoursSpecification, GeoCoordinates
Video pageVideoObjectArticle (if video is embedded in article)
Category / hub pageCollectionPageBreadcrumbList
EventEventOrganization, Place

Stacking rules:

  • Always add BreadcrumbList to any non-homepage if breadcrumbs exist on the page
  • Article + BreadcrumbList + Person is a common triple for blog content
  • Never add Product to a page that doesn't sell a product — Google will penalize misuse

Implementation Patterns

JSON-LD vs Microdata vs RDFa

Use JSON-LD. Full stop. Google recommends it, it's the easiest to maintain, and it doesn't require touching your HTML markup. Microdata and RDFa are legacy.

Placement
html
<head>
  <!-- All other meta tags -->
  <script type="application/ld+json">
  { ... your schema here ... }
  </script>
</head>

Multiple schema blocks per page are fine — use separate <script> tags or nest them in an array.

Per-Page vs Site-Wide
ScopeWhat to DoExample
Site-wideOrganization schema in site template headerYour company identity, logo, social profiles
Site-wideWebSite schema with SearchAction on homepageSitelinks search box
Per-pageContent-specific schemaArticle on blog posts, Product on product pages
Per-pageBreadcrumbList matching visible breadcrumbsEvery non-homepage

CMS implementation shortcuts:

  • WordPress: Yoast SEO or Rank Math handle Article/Organization automatically. Add custom schema via their blocks for HowTo/FAQ.
  • Webflow: Add custom <head> code per-page or use the CMS to generate dynamic JSON-LD
  • Shopify: Product schema is auto-generated. Add Organization and Article manually.
  • Custom CMS: Generate JSON-LD server-side with a template that pulls real field values
Reference patterns

See references/implementation-patterns.md for copy-paste JSON-LD for every schema type listed above.

Common Mistakes

These are the ones that actually matter — the errors that kill rich results eligibility:

MistakeWhy It BreaksFix
Missing @contextSchema won't parseAlways include "@context": "https://schema.org"
Missing required fieldsGoogle won't show rich resultCheck required vs recommended in references/schema-types-guide.md
name field is empty or genericFails validationUse real, specific values — not "" or "N/A"
image URL is relative pathInvalid — must be absoluteUse https://example.com/image.jpg not /image.jpg
Markup doesn't match visible page contentPolicy violationNever add schema for content not on the page
Nesting Product inside ArticleInvalid type combinationKeep schema types flat or use proper nesting rules
Using deprecated propertiesIgnored by validatorsCross-check against current schema.org — types evolve
Date in wrong formatFails ISO 8601 checkUse "2024-01-15" or "2024-01-15T10:30:00Z"
Show full SKILL.md (643 more words)Show less

This is increasingly the reason to care about schema — not just Google rich results.

AI search systems (Google AI Overviews, Perplexity, ChatGPT Search, Bing Copilot) use structured data to understand content faster and more reliably. When your content has clean schema:

  • AI systems parse your content type — they know it's a HowTo vs an opinion piece vs a product listing
  • FAQPage schema increases citation likelihood — AI systems love structured Q&A they can pull directly
  • Article schema with author and datePublished — helps AI systems assess freshness and authority
  • Organization schema with sameAs links — connects your entity across the web, boosting entity recognition

Practical actions for AI search visibility:

  1. Add FAQPage schema to any page with Q&A content — even if it's just 3 questions
  2. Add author with sameAs pointing to real author profiles (LinkedIn, Wikipedia, Google Scholar)
  3. Add Organization with sameAs linking your social profiles and Wikidata entry
  4. Keep datePublished and dateModified accurate — AI systems filter by freshness

Testing & Validation

Always test before publishing. Use all three:

  1. Google Rich Results Test — https://search.google.com/test/rich-results

    • Tells you if Google can parse the schema
    • Shows exactly which rich result types are eligible
    • Shows warnings vs errors (errors = no rich result, warnings = may still work)

  2. Schema.org Validator — https://validator.schema.org

    • Broader validation against the full schema.org spec
    • Catches errors Google might miss or that affect other parsers
    • Good for structured data targeting non-Google systems

  3. scripts/schema_validator.py — run locally on any HTML file

    • Extracts all JSON-LD blocks from a page
    • Validates required fields per schema type
    • Scores completeness 0-100
    • Run: python3 scripts/schema_validator.py page.html

  4. Google Search Console (after deployment)

    • Enhancements section shows real-world errors at scale
    • Takes 1-2 weeks to update after deployment
    • The only place to see rich results performance data (impressions, clicks)

Proactive Triggers

Surface these without being asked:

  • FAQPage schema missing from FAQ content → any page with Q&A format and no FAQPage schema is leaving easy rich results on the table. Flag it and offer to generate.
  • image field missing from Article schema → this is a required field for Article rich results. Google won't show the article card without it.
  • Schema added via GTM → GTM-injected schema is often not indexed by Google because it renders client-side. Recommend server-side injection.
  • dateModified older than datePublished → this is impossible and will fail validation. Flag and fix.
  • Multiple conflicting @type on same entity → e.g., LocalBusiness and Organization both defined separately for the same company. Should be combined or one should extend the other.
  • Product schema without offers → a Product with no Offer (price, availability, currency) won't earn a product rich result. Flag the missing Offer block.

Output Artifacts

When you ask for...You get...
Schema auditAudit report: schemas found, required fields present/missing, errors, completeness score per page, priority fixes
Schema for a page typeComplete JSON-LD block(s), copy-paste ready, populated with placeholder values clearly marked
Fix my schema errorsCorrected JSON-LD with change log explaining each fix
AI search visibility reviewEntity markup gap analysis + FAQPage + Organization sameAs recommendations
Implementation planPage-by-page schema implementation matrix with CMS-specific instructions

Communication

All output follows the structured communication standard:

  • Bottom line first — answer before explanation
  • What + Why + How — every finding has all three
  • Actions have owners and deadlines — no "we should consider"
  • Confidence tagging — 🟢 verified (test passed) / 🟡 medium (valid but untested) / 🔴 assumed (needs verification)
  • seo-audit: For full technical and content SEO audit. Use seo-audit when the problem spans more than just structured data. NOT for schema-specific work — use schema-markup.
  • site-architecture: For URL structure, internal linking, and navigation. Use when architecture is the root cause of SEO problems, not schema.
  • content-strategy: For what content to create. Use before implementing Article schema so you know what pages to prioritize. NOT for the schema itself.
  • programmatic-seo: For sites with thousands of pages that need schema at scale. Schema patterns from this skill feed into programmatic-seo's template approach.

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

Files

SKILL.md and 3 other files (scripts, references) in marketing-skill/skills/schema-markup of alirezarezvani/claude-skills.

  • SKILL.md
  • references/implementation-patterns.md
  • references/schema-types-guide.md
  • scripts/schema_validator.py

Open the folder on GitHubat commit 19392f7

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in alirezarezvani/claude-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Schema Markup 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.

Schema Markup compared with similar skills
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SEO Auditfreekmurze/dotfiles1k33 repos~2.2kAutomated safety check: PassNone
Google Search SEO Guidelittleben/awesomeAgentskills1882 repos~4.2kAutomated safety check: PassMIT
Global SEO Growthminhnv0807/ai-business-skills608—~5kAutomated safety check: PassMIT

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Works with

Categories

Questions about Schema Markup

What does Schema Markup do?

When the user wants to implement, audit, or validate structured data (schema markup) on their website. Schema Markup is an agent skill from alirezarezvani/claude-skills. When the user wants to implement, audit, or validate structured data (schema markup) on their website.

When should I use Schema Markup?

Schema Markup fits situations like: wants to implement; validate structured data (schema markup) on their website; the user mentions structured data; structured data errors in Search Console. Also use when someone asks why their content isnt showing rich results.

How do I install Schema Markup in Claude Code?

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

How do I install Schema Markup in Codex?

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

Can I use Schema Markup 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 alirezarezvani/claude-skills --skill schema-markup -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/schema-markup, .gemini/skills/schema-markup, .github/skills/schema-markup and .opencode/skills/schema-markup in your project.

What does Schema Markup need to run?

Going by SKILL.md and its folder, Schema Markup needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Schema Markup access the network?

SKILL.md names 3 domains. In commands or code: schema.org, search.google.com and validator.schema.org; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Schema Markup safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Schema Markup use?

Schema Markup is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Schema Markup use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.1k tokens, read only when the agent opens those files.

What are the alternatives to Schema Markup?

Skills that share tags, products or a category with Schema Markup: SEO Audit with Search Console (nowork-studio/notfair-plugin, 3.9k stars), SEO Setup (alisamadiii/Portfolio, 180 stars), SEO Audit (freekmurze/dotfiles, 1k stars) and Google Search SEO Guide (littleben/awesomeAgentskills, 188 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Schema Markup?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,788 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

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