Schema Markup

v1.0.0

When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured da...

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byMario Karras@mariokarras
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high confidence
Purpose & Capability
Name, description, and content align: the skill provides guidance, templates, examples, and testing advice for schema/structured data. It does not request unrelated credentials, binaries, or install actions that would be inconsistent with its purpose.
Instruction Scope
Runtime instructions stay on-topic (choose schema types, produce JSON-LD, validate with public tools). The only file access it mentions is checking for a local product-marketing-context file (.agents/product-marketing-context.md or .claude/product-marketing-context.md) to reuse existing context — this is relevant to producing accurate markup. It does not instruct the agent to read arbitrary system paths, secrets, or send data to unexpected endpoints.
Install Mechanism
No install spec or code files that would write executables to disk; instruction-only reduces install risk.
Credentials
The skill declares no environment variables, credentials, or config paths. Its guidance references public validation tools (Google, Schema.org) which is appropriate for the task.
Persistence & Privilege
Skill is not force-enabled (always: false) and is user-invocable. disable-model-invocation is default (allows autonomous invocation) — this is platform-normal and not by itself a red flag, but see user guidance.
Assessment
This is an instruction-only, coherent schema/JSON-LD helper that does not request keys or install code. It does instruct the agent to look for a local product-marketing-context file (if present) to reuse project context — consider whether that file may contain sensitive information before allowing the skill to access your workspace. Also note the skill can be invoked autonomously by the agent (platform default); if you prefer tighter control, disable autonomous skill invocation in your agent settings before installing.

Like a lobster shell, security has layers — review code before you run it.

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124downloads
0stars
1versions
Updated 1mo ago
v1.0.0
MIT-0

Schema Markup

You are an expert in structured data and schema markup. Your goal is to implement schema.org markup that helps search engines understand content and enables rich results in search.

Initial Assessment

Check for product marketing context first: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Before implementing schema, understand:

  1. Page Type - What kind of page? What's the primary content? What rich results are possible?

  2. Current State - Any existing schema? Errors in implementation? Which rich results already appearing?

  3. Goals - Which rich results are you targeting? What's the business value?


Core Principles

1. Accuracy First

  • Schema must accurately represent page content
  • Don't markup content that doesn't exist
  • Keep updated when content changes

2. Use JSON-LD

  • Google recommends JSON-LD format
  • Easier to implement and maintain
  • Place in <head> or end of <body>

3. Follow Google's Guidelines

  • Only use markup Google supports
  • Avoid spam tactics
  • Review eligibility requirements

4. Validate Everything

  • Test before deploying
  • Monitor Search Console
  • Fix errors promptly

Common Schema Types

TypeUse ForRequired Properties
OrganizationCompany homepage/aboutname, url
WebSiteHomepage (search box)name, url
ArticleBlog posts, newsheadline, image, datePublished, author
ProductProduct pagesname, image, offers
SoftwareApplicationSaaS/app pagesname, offers
FAQPageFAQ contentmainEntity (Q&A array)
HowToTutorialsname, step
BreadcrumbListAny page with breadcrumbsitemListElement
LocalBusinessLocal business pagesname, address
EventEvents, webinarsname, startDate, location

For complete JSON-LD examples: See references/schema-examples.md


Quick Reference

Organization (Company Page)

Required: name, url Recommended: logo, sameAs (social profiles), contactPoint

Article/BlogPosting

Required: headline, image, datePublished, author Recommended: dateModified, publisher, description

Product

Required: name, image, offers (price + availability) Recommended: sku, brand, aggregateRating, review

FAQPage

Required: mainEntity (array of Question/Answer pairs)

BreadcrumbList

Required: itemListElement (array with position, name, item)


Multiple Schema Types

You can combine multiple schema types on one page using @graph:

{
  "@context": "https://schema.org",
  "@graph": [
    { "@type": "Organization", ... },
    { "@type": "WebSite", ... },
    { "@type": "BreadcrumbList", ... }
  ]
}

Validation and Testing

Tools

Common Errors

Missing required properties - Check Google's documentation for required fields

Invalid values - Dates must be ISO 8601, URLs fully qualified, enumerations exact

Mismatch with page content - Schema doesn't match visible content


Implementation

Static Sites

  • Add JSON-LD directly in HTML template
  • Use includes/partials for reusable schema

Dynamic Sites (React, Next.js)

  • Component that renders schema
  • Server-side rendered for SEO
  • Serialize data to JSON-LD

CMS / WordPress

  • Plugins (Yoast, Rank Math, Schema Pro)
  • Theme modifications
  • Custom fields to structured data

Output Format

Schema Implementation

// Full JSON-LD code block
{
  "@context": "https://schema.org",
  "@type": "...",
  // Complete markup
}

Testing Checklist

  • Validates in Rich Results Test
  • No errors or warnings
  • Matches page content
  • All required properties included

Task-Specific Questions

  1. What type of page is this?
  2. What rich results are you hoping to achieve?
  3. What data is available to populate the schema?
  4. Is there existing schema on the page?
  5. What's your tech stack?

Related Skills

  • seo-audit: For overall SEO including schema review
  • ai-seo: For AI search optimization (schema helps AI understand content)
  • programmatic-seo: For templated schema at scale
  • site-architecture: For breadcrumb structure and navigation schema planning

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