Add, fix, and optimize schema markup to enable rich search results and help search engines understand page content.
Works with
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
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionschema-markupExecute the skills CLI command in your project's root directory to begin installation:
Fetches schema-markup from coreyhaines31/marketingskills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate schema-markup. Access via /schema-markup in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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.
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:
Page Type - What kind of page? What's the primary content? What rich results are possible?
Current State - Any existing schema? Errors in implementation? Which rich results already appearing?
Goals - Which rich results are you targeting? What's the business value?
<head> or end of <body>| 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
Required: name, url Recommended: logo, sameAs (social profiles), contactPoint
Required: headline, image, datePublished, author Recommended: dateModified, publisher, description
Required: name, image, offers (price + availability) Recommended: sku, brand, aggregateRating, review
Required: mainEntity (array of Question/Answer pairs)
Required: itemListElement (array with position, name, item)
You can combine multiple schema types on one page using @graph:
{
"@context": "https://schema.org",
"@graph": [
{ "@type": "Organization", ... },
{ "@type": "WebSite", ... },
{ "@type": "BreadcrumbList", ... }
]
}
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
// Full JSON-LD code block
{
"@context": "https://schema.org",
"@type": "...",
// Complete markup
}
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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ailabs-393/ai-labs-claude-skills
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schema-markup is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
schema-markup fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for schema-markup matched our evaluation — installs cleanly and behaves as described in the markdown.
Registry listing for schema-markup matched our evaluation — installs cleanly and behaves as described in the markdown.
schema-markup is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
schema-markup reduced setup friction for our internal harness; good balance of opinion and flexibility.
schema-markup reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend schema-markup for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
I recommend schema-markup for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
schema-markup has been reliable in day-to-day use. Documentation quality is above average for community skills.
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