#601

Globales Ranking · von 601 Skills

schema-markup AI Agent Skill

Quellcode ansehen: coreyhaines31/marketingskills

Safe

Installation

npx skills add coreyhaines31/marketingskills --skill schema-markup

27.5K

Installationen

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

Type Use For Required Properties
Organization Company homepage/about name, url
WebSite Homepage (search box) name, url
Article Blog posts, news headline, image, datePublished, author
Product Product pages name, image, offers
SoftwareApplication SaaS/app pages name, offers
FAQPage FAQ content mainEntity (Q&A array)
HowTo Tutorials name, step
BreadcrumbList Any page with breadcrumbs itemListElement
LocalBusiness Local business pages name, address
Event Events, webinars name, 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

Installationen

Installationen 27.5K
Globales Ranking #601 von 601

Sicherheitsprüfung

ath Safe
socket Safe
Warnungen: 0 Bewertung: 90
snyk Low

So verwenden Sie diesen Skill

1

Install schema-markup by running npx skills add coreyhaines31/marketingskills --skill schema-markup in your project directory. Führen Sie den obigen Installationsbefehl in Ihrem Projektverzeichnis aus. Die Skill-Datei wird von GitHub heruntergeladen und in Ihrem Projekt platziert.

2

Keine Konfiguration erforderlich. Ihr KI-Agent (Claude Code, Cursor, Windsurf usw.) erkennt installierte Skills automatisch und nutzt sie als Kontext bei der Code-Generierung.

3

Der Skill verbessert das Verständnis Ihres Agenten für schema-markup, und hilft ihm, etablierte Muster zu befolgen, häufige Fehler zu vermeiden und produktionsreifen Code zu erzeugen.

Was Sie erhalten

Skills sind Klartext-Anweisungsdateien — kein ausführbarer Code. Sie kodieren Expertenwissen über Frameworks, Sprachen oder Tools, das Ihr KI-Agent liest, um seine Ausgabe zu verbessern. Das bedeutet null Laufzeit-Overhead, keine Abhängigkeitskonflikte und volle Transparenz: Sie können jede Anweisung vor der Installation lesen und prüfen.

Kompatibilität

Dieser Skill funktioniert mit jedem KI-Coding-Agenten, der das skills.sh-Format unterstützt, einschließlich Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider und anderen Tools, die projektbezogene Kontextdateien lesen. Skills sind auf Transportebene framework-agnostisch — der Inhalt bestimmt, für welche Sprache oder welches Framework er gilt.

Data sourced from the skills.sh registry and GitHub. Install counts and security audits are updated regularly.

EU Made in Europe

Chat with 100+ AI Models in one App.

Use Claude, ChatGPT, Gemini alongside with EU-Hosted Models like Deepseek, GLM-5, Kimi K2.5 and many more.