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schema-markup▌

coreyhaines31/marketingskills · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/coreyhaines31/marketingskills --skill schema-markup
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summary

Add, fix, and optimize schema markup to enable rich search results and help search engines understand page content.

  • ›Covers all major schema types: Organization, Article, Product, FAQPage, HowTo, BreadcrumbList, LocalBusiness, Event, and SoftwareApplication with required and recommended properties
  • ›Uses JSON-LD format (Google's recommended approach) with support for multiple schema types on one page via @graph
  • ›Includes validation against Google Rich Results Test and Schema.org Validato
skill.md

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
how to use schema-markup

How to use schema-markup on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • ›Cursor installed and configured on your development machine
  • ›Node.js version 16.0+ with npm package manager (verify with node --version)
  • ›Active project directory or workspace where you want to add schema-markup
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/coreyhaines31/marketingskills --skill schema-markup

The skills CLI fetches schema-markup from GitHub repository coreyhaines31/marketingskills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/schema-markup

Reload or restart Cursor to activate schema-markup. Access the skill through slash commands (e.g., /schema-markup) or your agent's skill management interface.

⚠

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

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Use Cases▌

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

✓

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

✓

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

✓

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

✓

Save 3-5 hours/week on communication overhead

Implementation Guide▌

Prerequisites

  • ›Claude Desktop or compatible AI client
  • ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • ›Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • ⚠Not validating competitive research—verify facts before sharing
  • ⚠Accepting user stories without involving engineering team
  • ⚠Over-relying on frameworks without qualitative judgment
  • ⚠Not customizing outputs to company culture and communication style
  • ⚠Skipping stakeholder validation of generated requirements

Best Practices▌

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • −Don't publish competitive analysis without fact-checking
  • −Don't finalize user stories without engineering review
  • −Don't make prioritization decisions solely on AI scoring
  • −Don't skip customer validation of generated requirements
  • −Don't ignore company-specific context and culture

💡 Pro Tips

  • ★Provide context: company goals, constraints, customer feedback
  • ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • ★Use skill for 70% generation + 30% customization to company needs

When to Use This▌

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path▌

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.5★★★★★50 reviews
  • ★★★★★Ama Haddad· Dec 28, 2024

    schema-markup is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Kaira Martinez· Dec 24, 2024

    schema-markup fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Chaitanya Patil· Dec 16, 2024

    Registry listing for schema-markup matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Hana Srinivasan· Dec 16, 2024

    Registry listing for schema-markup matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Luis Mensah· Nov 11, 2024

    schema-markup is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Piyush G· Nov 7, 2024

    schema-markup reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Hiroshi Mensah· Nov 7, 2024

    schema-markup reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Shikha Mishra· Oct 26, 2024

    I recommend schema-markup for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • ★★★★★Hiroshi Perez· Oct 26, 2024

    I recommend schema-markup for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • ★★★★★Carlos Reddy· Oct 18, 2024

    schema-markup has been reliable in day-to-day use. Documentation quality is above average for community skills.

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