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Documentation Index

Fetch the complete documentation index at: https://docs.getcore.me/llms.txt

Use this file to discover all available pages before exploring further.

Goal: Implement schema.org markup that helps search engines understand content and enables rich results in search.

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Tools Required

This skill runs using CORE memory only. No integrations required.

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Trigger

Run on demand when the user wants to add or audit schema markup.

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Setup

Search memory for:
  • “What pages need schema?”
  • “What rich results are you targeting?”
  • “What’s your tech stack?”
If nothing found, ask once:
“What type of pages are you optimizing? (1) Blog / Product / FAQs / Other? (2) What rich results do you want to appear? (3) What’s your tech stack?”
Store the response in memory. Do not ask again in future runs.

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Step 1: Determine Relevant Schema Types

Match page type to schema:
Page TypeSchema TypeRich Result
Blog postArticleTitle, image, date
Product pageProductPrice, availability, rating
Company pageOrganizationLogo, contact, social
FAQ pageFAQPageQuestion/answer pairs
How-to guideHowToSteps with images
EventEventDate, time, location
Local businessLocalBusinessAddress, hours, phone
Software/SaaSSoftwareApplicationOffer, rating
Choose the most relevant type(s) for your page.

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Step 2: Gather Required Data

For your chosen schema type, collect required properties: Article: headline, image, datePublished, author, description Product: name, image, offers (price + availability), sku, brand FAQPage: mainEntity (array of Q&A pairs with name and text properties) BreadcrumbList: itemListElement (array with position, name, item URL) Organization: name, url, logo, contactPoint (phone/email) Not all properties are required, but more complete data produces better rich results.

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Step 3: Write JSON-LD Markup

Structure your schema as JSON-LD in the <head> or end of <body>: 
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Page Headline",
  "image": "https://example.com/image.jpg",
  "datePublished": "2024-01-15T12:00:00Z",
  "author": {
    "@type": "Person",
    "name": "Author Name"
  },
  "description": "Brief description"
}
For multiple schema types on one page, use @graph: 
{
  "@context": "https://schema.org",
  "@graph": [
    { "@type": "Organization", ... },
    { "@type": "BreadcrumbList", ... }
  ]
}

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Step 4: Handle Dynamic Content

If content is dynamic (React, Next.js):
  • Render schema server-side for SEO
  • Serialize page data to JSON-LD
  • Test in Rich Results Test Tool after server rendering
For static sites:
  • Add JSON-LD directly in HTML template
  • Use includes/partials for reusable schema
For WordPress/CMS:
  • Use plugins (Yoast, Rank Math, Schema Pro)
  • Customize via theme or custom code

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Step 5: Validate and Test

Use these tools: Check for:
  • ✓ All required properties included
  • ✓ Correct property types and formats
  • ✓ No validation errors or warnings
  • ✓ Dates in ISO 8601 format (YYYY-MM-DDTHH:MM:SSZ)
  • ✓ URLs fully qualified (https://example.com, not /path)

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Step 6: Monitor and Maintain

After deployment:
  • Check Search Console Enhancements report
  • Monitor for errors
  • Update schema when content changes
  • Avoid stale dates or deprecated properties

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Output Format

Schema Markup Implementation — [Page/Site Name] Page Analysis
  • Page type: [Blog / Product / FAQ / Other]
  • Target rich results: [What should appear in search]
  • Current schema status: [None / Partial / Needs update]
Recommended Schema Types
  1. [Type]: [Why this helps]
  2. [Type]: [Why this helps]
JSON-LD Code 
{
  "@context": "https://schema.org",
  "@type": "...",
  // [Full code block here]
}
Required Data Checklist
  • [Property]: [Planned value or source]
  • [Property]: [Planned value or source]
  • [Property]: [Planned value or source]
Implementation Plan
  • Static / Dynamic: [How content is delivered]
  • Placement: [<head> or end of <body>]
  • Testing: [Rich Results Test pass?]
Rich Results Expected
  • [What should appear in search results]
  • [Examples or screenshots if helpful]

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Edge Cases

  • Content changes frequently: Update schema dynamically when content updates
  • Multiple languages: Add lang attribute; use hreflang for multi-language sites
  • Multiple product prices (regional): Use priceCurrency to specify region
  • No author name: Use organization name instead; don’t leave blank
  • Future-dated content (embargo): Date must match actual publication; don’t pre-add schema
  • Review schema with few ratings: Only add when >10 genuine reviews to avoid appearing artificial