Schema Markup
FreeImplement and validate structured data for rich search results.
Free · Opens the source repo
What Schema Markup does
The Schema Markup skill is designed for developers and webmasters looking to implement, audit, and validate structured data on their websites. By utilizing schema.org markup, this skill helps users enhance their content's visibility in search engines, enabling rich results that can improve click-through rates. Whether you're adding new schema or fixing existing markup, this skill provides a structured approach to ensure your data is correctly formatted and compliant with Google's guidelines.
This skill operates in three distinct modes: auditing existing markup, implementing new schema, and validating and fixing current schema. In audit mode, users can run a validation script to identify existing schema on their pages, cross-reference errors with Google's Search Console, and generate a comprehensive report detailing what is functioning and what needs attention. For implementation, the skill guides users through selecting the appropriate schema types, populating JSON-LD templates with real content, and advising on the best practices for placement within the HTML.
In validation mode, the skill checks existing schema against Google's rich results requirements, identifies errors, and provides corrected JSON-LD code. This ensures that users not only fix issues but also understand the rationale behind the corrections, preventing future mistakes. The skill emphasizes the importance of using JSON-LD, as it is the preferred format for structured data according to Google, making it easier to maintain and implement.
Overall, this skill is ideal for web developers, digital marketers, and SEO specialists who want to leverage structured data to enhance their site's performance in search results. By following the guidelines and utilizing the resources provided, users can effectively improve their content's search visibility and user engagement.
When to use it
Use this skill when you need to add or troubleshoot schema markup on your website to achieve rich search results.
When not to use it
This skill is not suitable for general SEO audits or technical crawl issues; those should be handled by dedicated SEO tools.
What you can build with it
Adding FAQ Schema
When creating a new FAQ page, use this skill to implement structured data that enhances visibility in search results.
Fixing Schema Errors
If Google Search Console reports errors in your existing schema, use this skill to validate and correct the markup.
Implementing Product Schema
For an e-commerce site, utilize this skill to add structured data to product pages, improving their chances of appearing with rich snippets.
How to install Schema Markup
View source1. Install with the skills CLI
npx skills add alirezarezvani/claude-skills/schema-markup --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by alirezarezvaniSchema 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.
- Run
scripts/schema_validator.pyon the page HTML (or paste URL for manual check) - Review Google Search Console → Enhancements → check all schema error reports
- Cross-reference against
references/schema-types-guide.mdfor required fields - 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.
- Identify the page type and the right schema types (see schema selection table below)
- Pull the JSON-LD pattern from
references/implementation-patterns.md - Populate with real page content
- Advise on placement (inline
<script>in<head>, CMS plugin, GTM injection) - 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.
- Test at rich-results.google.com and validator.schema.org
- Map errors to specific missing or malformed fields
- Deliver corrected JSON-LD with the broken fields fixed
- 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 Type | Primary Schema | Supporting Schema |
|---|---|---|
| Homepage | Organization | WebSite (with SearchAction) |
| Blog post / article | Article | BreadcrumbList, Person (author) |
| How-to guide | HowTo | Article, BreadcrumbList |
| FAQ page | FAQPage | — |
| Product page | Product | Offer, AggregateRating, BreadcrumbList |
| Local business | LocalBusiness | OpeningHoursSpecification, GeoCoordinates |
| Video page | VideoObject | Article (if video is embedded in article) |
| Category / hub page | CollectionPage | BreadcrumbList |
| Event | Event | Organization, Place |
Stacking rules:
- Always add
BreadcrumbListto any non-homepage if breadcrumbs exist on the page Article+BreadcrumbList+Personis a common triple for blog content- Never add
Productto 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
<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
| Scope | What to Do | Example |
|---|---|---|
| Site-wide | Organization schema in site template header | Your company identity, logo, social profiles |
| Site-wide | WebSite schema with SearchAction on homepage | Sitelinks search box |
| Per-page | Content-specific schema | Article on blog posts, Product on product pages |
| Per-page | BreadcrumbList matching visible breadcrumbs | Every 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:
| Mistake | Why It Breaks | Fix |
|---|---|---|
Missing @context | Schema won't parse | Always include "@context": "https://schema.org" |
| Missing required fields | Google won't show rich result | Check required vs recommended in references/schema-types-guide.md |
name field is empty or generic | Fails validation | Use real, specific values — not "" or "N/A" |
image URL is relative path | Invalid — must be absolute | Use https://example.com/image.jpg not /image.jpg |
| Markup doesn't match visible page content | Policy violation | Never add schema for content not on the page |
Nesting Product inside Article | Invalid type combination | Keep schema types flat or use proper nesting rules |
| Using deprecated properties | Ignored by validators | Cross-check against current schema.org — types evolve |
| Date in wrong format | Fails ISO 8601 check | Use "2024-01-15" or "2024-01-15T10:30:00Z" |
Schema and AI Search
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
authoranddatePublished— helps AI systems assess freshness and authority - Organization schema with
sameAslinks — connects your entity across the web, boosting entity recognition
Practical actions for AI search visibility:
- Add FAQPage schema to any page with Q&A content — even if it's just 3 questions
- Add
authorwithsameAspointing to real author profiles (LinkedIn, Wikipedia, Google Scholar) - Add
OrganizationwithsameAslinking your social profiles and Wikidata entry - Keep
datePublishedanddateModifiedaccurate — AI systems filter by freshness
Testing & Validation
Always test before publishing. Use all three:
-
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)
-
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
-
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
-
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.
imagefield 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.
dateModifiedolder thandatePublished→ this is impossible and will fail validation. Flag and fix.- Multiple conflicting
@typeon same entity → e.g.,LocalBusinessandOrganizationboth 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 audit | Audit report: schemas found, required fields present/missing, errors, completeness score per page, priority fixes |
| Schema for a page type | Complete JSON-LD block(s), copy-paste ready, populated with placeholder values clearly marked |
| Fix my schema errors | Corrected JSON-LD with change log explaining each fix |
| AI search visibility review | Entity markup gap analysis + FAQPage + Organization sameAs recommendations |
| Implementation plan | Page-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)
Related Skills
- 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.
Frequently asked questions about Schema Markup
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