Generate Schema.org JSON-LD markup for search engine rich results and AI understanding.
Works with
Supports 10+ schema types including FAQPage, HowTo, Article, Product, LocalBusiness, Organization, BreadcrumbList, Event, and Recipe with validation against Google Rich Results requirements
Maps content to appropriate schema types based on page purpose (blog, product, FAQ, local business, etc.) and identifies eligible rich result opportunities
Generates valid JSON-LD with all required and optional
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionschema-markup-generatorExecute the skills CLI command in your project's root directory to begin installation:
Fetches schema-markup-generator from aaron-he-zhu/seo-geo-claude-skills 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-generator. Access via /schema-markup-generator 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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SEO & GEO Skills Library · 20 skills for SEO + GEO · ClawHub · skills.sh System Mode: This build skill follows the shared Skill Contract and State Model.
This skill creates Schema.org structured data markup in JSON-LD format to help search engines understand your content and enable rich results in SERPs.
System role: Build layer skill. It turns briefs and signals into assets that other skills can review, publish, and monitor.
Use this when the conversation involves any of these situations — even if the user does not use SEO terminology:
Use this whenever the task needs a shippable asset or transformation that should feed directly into quality review, deployment, or monitoring.
Start with one of these prompts. Finish with a short handoff summary using the repository format in Skill Contract.
Generate schema markup for this [content type]: [content/URL]
Create FAQ schema for these questions and answers: [Q&A list]
Create Product schema for [product name] with [details]
Generate LocalBusiness schema for [business name and details]
Review and improve this schema markup: [existing schema]
Expected output: a ready-to-use asset or implementation-ready transformation plus a short handoff summary ready for memory/content/.
memory/content/.CLAUDE.md, memory/decisions.md, and memory/open-loops.md.Next Best Skill below when the asset is ready for review or deployment.See CONNECTORS.md for tool category placeholders.
With ~~web crawler connected: Automatically crawl and extract page content (visible text, headings, lists, tables), existing schema markup, page metadata, and structured content elements that map to schema properties.
With manual data only: Ask the user to provide:
Proceed with the full workflow using provided data. Note in the output which data is from automated extraction vs. user-provided data.
When a user requests schema markup:
Identify Content Type and Rich Result Opportunity
Reference the CORE-EEAT Benchmark item O05 (Schema Markup) for content-type to schema mapping:
### CORE-EEAT Schema Mapping (O05)
| Content Type | Required Schema | Conditional Schema |
|-------------|----------------|--------------------|
| Blog (guides) | Article, Breadcrumb | FAQ, HowTo |
| Blog (tools) | Article, Breadcrumb | FAQ, Review |
| Blog (insights) | Article, Breadcrumb | FAQ |
| Alternative | Comparison*, Breadcrumb, FAQ | AggregateRating |
| Best-of | ItemList, Breadcrumb, FAQ | AggregateRating per tool |
| Use-case | WebPage, Breadcrumb, FAQ | — |
| FAQ | FAQPage, Breadcrumb | — |
| Landing | SoftwareApplication, Breadcrumb, FAQ | WebPage |
| Testimonial | Review, Breadcrumb | FAQ, Person |
*Use the mapping above to ensure schema type matches content type (CORE-EEAT O05: Pass criteria).*
### Schema Analysis
**Content Type**: [blog/product/FAQ/how-to/local business/etc.]
**Page URL**: [URL]
**Eligible Rich Results**:
| Rich Result Type | Eligibility | Impact |
|------------------|-------------|--------|
| FAQ | ✅/❌ | High - Expands SERP presence |
| How-To | ✅/❌ | Medium - Shows steps in SERP |
| Product | ✅/❌ | High - Shows price, availability |
| Review | ✅/❌ | High - Shows star ratings |
| Article | ✅/❌ | Medium - Shows publish date, author |
| Breadcrumb | ✅/❌ | Medium - Shows navigation path |
| Video | ✅/❌ | High - Shows video thumbnail |
**Recommended Schema Types**:
1. [Primary schema type] - [reason]
2. [Secondary schema type] - [reason]
Generate Schema Markup
Based on the identified content type, generate the appropriate JSON-LD schema. Supported types: FAQPage, HowTo, Article/BlogPosting/NewsArticle, Product, LocalBusiness, Organization, BreadcrumbList, Event, Recipe, and combined multi-type schemas.
Reference: See references/schema-templates.md for complete, copy-ready JSON-LD templates for all schema types with required and optional properties.
For each schema generated, include:
When combining multiple schema types on one page, wrap them in a JSON array inside a single <script type="application/ld+json"> tag.
Provide Implementation and Validation
## Implementation Guide
### Adding Schema to Your Page
**Option 1: In HTML <head>**
```html
<head>
<script type="application/ld+json">
[Your JSON-LD schema here]
</script>
</head>
Option 2: Before closing
<script type="application/ld+json">
[Your JSON-LD schema here]
</script>
</body>
~~schema validator
Schema.org Validator
~~search console
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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Useful defaults in schema-markup-generator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
schema-markup-generator is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend schema-markup-generator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
schema-markup-generator reduced setup friction for our internal harness; good balance of opinion and flexibility.
schema-markup-generator reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend schema-markup-generator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: schema-markup-generator is focused, and the summary matches what you get after install.
Keeps context tight: schema-markup-generator is the kind of skill you can hand to a new teammate without a long onboarding doc.
schema-markup-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
schema-markup-generator has been reliable in day-to-day use. Documentation quality is above average for community skills.
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