What does the Structured Data AI skill do?

Schema.org Structured Data Reference — JSON-LD examples for every major schema type, rich results eligibility, testing tools, and implementation patterns

Why use Structured Data on TypingMind?

Because you install it once and use it with any model. Structured Data is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Structured Data in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cognyai/claude-code-marketing-skills/tree/main/skills/structured-data. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Structured Data?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Structured Data?

As many as you like. As long as a model supports skills, you can use Structured Data with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Structured Data AI skill free?

It is published on GitHub by cognyai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Structured Data by cognyai — AI Skill for Any LLM

Schema.org Structured Data Reference

Complete reference for Schema.org structured data markup: JSON-LD examples, rich results eligibility, testing tools, validation, and implementation patterns for static sites, Next.js, React, and WordPress.

Full docs: https://cogny.com/docs/structured-data-reference

Usage


/structured-data                          # Full reference overview
/structured-data Product                  # Show Product schema example
/structured-data FAQPage                  # Show FAQPage example (no longer a Google rich result)
/structured-data audit <url>              # Fetch a live page, extract its JSON-LD, flag errors
/structured-data LocalBusiness            # Show LocalBusiness example
/structured-data validate                 # Testing and validation guide
/structured-data best-practices           # Schema best practices
/structured-data rich-results             # Rich results eligibility table

Instructions

You are a Schema.org structured data expert. Use this reference to help users write correct JSON-LD markup, choose the right schema type for their pages, validate their structured data, and implement it across different platforms.

When the user asks a question, find the relevant section below and provide precise, actionable answers with ready-to-use JSON-LD examples.

If the user provides a specific schema type or topic as an argument, focus on that area. Otherwise, provide an overview and help them determine which schema type they need.

If Cogny isn't connected, skip the Search Console steps below and note what connecting adds (which pages actually earn rich results, Google's own parse of the URL).

When Search Console MCP tools are available, use them to:

Check which pages have rich results via tool_get_search_analytics (filter by search appearance)
Inspect specific URLs for structured data issues via tool_inspect_url
List properties to identify which sites to audit via tool_list_properties

Works with

Writing and validating JSON-LD needs no accounts. Connected providers let you build markup from the real source data instead of a template, and check it in both search engines.

Job	Primary	Also answers it	No account
Is markup seen / rich results earned	Google Search Console (`tool_inspect_url`, `tool_get_search_analytics`)	Bing Webmaster (`tool_get_url_info`, `tool_get_crawl_issues`)	`/structured-data audit <url>` (curl), Schema Markup Validator; Rich Results Test needs a browser
Product, Offer, AggregateRating values	Shopify (`tool_list_products`, `tool_get_product`, `tool_get_metafields` for review data)	WooCommerce (`list_products`, `list_product_variations`, `list_product_reviews`)	WebFetch the product page
Article / BlogPosting values	WordPress (`list_posts`), Ghost (`list_posts`), Sanity (`tool_list_documents`), Contentful (`contentful_list_entries`)	—	WebFetch the article

Enhanced when a store or CMS is connected: If Cogny isn't connected, skip this and note what connecting adds (markup built from the real catalogue or CMS, and drift between source data and live markup).

Pull the items (all tools take the mcp__cogny__mcp__<Prefix>__ prefix, e.g. mcp__cogny__mcp__Shopify__tool_list_products with first: 50).
Map fields to schema: title → name, price + currency → offers.price / priceCurrency (from the store, never assumed USD), inventory → availability, SKU/GTIN → sku/gtin, published/updated dates → datePublished/dateModified.
Fetch each live page with Bash curl (WebFetch summarises and drops <script> blocks) and diff its JSON-LD against the source: wrong price, stale availability or a rating that doesn't match the reviews are policy risks, not just bugs.
Output a fix list plus ready-to-paste JSON-LD per template (not per item).

Writing markup back (Shopify__tool_set_metafields, CMS updates) or pushing it to Bing (Bing_Webmaster_Tools__tool_submit_content with structured_data) are writes: draft them and ask first.

Audit a live page (`/structured-data audit <url>`)

Works with zero accounts. WebFetch can't see <head> or <script> content, so use curl:

bash
U="<url>"
curl -sL -A "Mozilla/5.0" "$U" -o page.html
python3 -I - page.html <<'PY'
import json, re, sys
html = open(sys.argv[1], encoding="utf-8", errors="replace").read()
blocks = re.findall(r'<script[^>]+application/ld\+json[^>]*>(.*?)</script>', html, re.S | re.I)
print(f"{len(blocks)} JSON-LD block(s)")
for i, b in enumerate(blocks):
    try:
        print(f"--- block {i}\n" + json.dumps(json.loads(b), indent=2)[:4000])
    except ValueError as e:
        print(f"--- block {i}: INVALID JSON ({e})")
PY

Then validate each entity against the type's section below and Google's docs, and check for these common errors:

Check	How	Why it matters
JSON parses	Script above	One syntax error drops the whole block
Required properties present	Compare with the type section below	Missing required = no rich result
`logo` / `image` URLs resolve	`curl -sI -o /dev/null -w "%{http_code} %{content_type}\n" <url>` on each	A 404 logo or an HTML page served as `image` is a common, silent failure
Prices consistent	`offers.price` vs the price visible in the HTML vs other blocks (e.g. Product vs `@graph` duplicates, plugin + theme both emitting markup)	Mismatched prices violate Google's Product guidelines
`price` numeric, `priceCurrency` ISO 4217	Inspect	`"$49"` is invalid
Self-serving `AggregateRating`	`aggregateRating` on the site's own `Organization` / `LocalBusiness` (reviews it controls about itself)	Ineligible for star snippets per Google's review-snippet guidelines
Rating with no visible reviews	Grep the HTML for the review count/stars	Markup must match visible content
`dateModified` = build/deploy time	Fetch 2-3 pages (and the same page twice a day apart); identical timestamps across unrelated pages, or always "now", mean it's generated at build	Misleading freshness signal; set it from the content's real edit date
`datePublished` after `dateModified`, or in the future	Compare	Validation warning
Relative URLs	Any `url`/`image`/`@id` not starting `https://`	Use absolute URLs
Deprecated types	`HowTo`, `FAQPage`	No Google rich result (see eligibility table); harmless, but don't promise one
Duplicate entities	Two `Organization` or `Product` blocks with different values	Conflicting signals

Paste the extracted JSON into the Schema Markup Validator (https://validator.schema.org, works on code snippets) for a vocabulary check. The Google Rich Results Test (https://search.google.com/test/rich-results) renders the page in a browser and has no public API: give the user the link to run it rather than claiming a pass. Output a table of findings (severity, entity, property, fix) plus corrected JSON-LD.

What Structured Data Does

Structured data is machine-readable markup that tells search engines, voice assistants, and AI systems exactly what your page content means. You declare it explicitly using the Schema.org vocabulary.

Benefits:

Rich results — star ratings, prices, event listings, breadcrumbs in Google Search (FAQ and HowTo rich results have been retired; see the eligibility table)
Knowledge panels — branded panels for organizations, people, and products
Voice search — direct answers in Google Assistant and other voice interfaces
AI citations — LLMs and AI search engines (Google AI Overviews, Bing Copilot, Perplexity) use structured data to surface and attribute information

Formats

Three formats exist. Google explicitly recommends JSON-LD.

JSON-LD (Recommended)

html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Example Corp"
}
</script>

Why JSON-LD: Decoupled from HTML, injectable by JS frameworks, easy to validate, no layout risk.

Microdata

Inline HTML attributes (itemscope, itemtype, itemprop). Use only in legacy systems that cannot add <script> tags.

RDFa

Inline attributes (vocab, typeof, property). Rare on the web — more common in XML/SVG contexts.

Bottom line: Use JSON-LD for all new implementations.

Schema Types with JSON-LD Examples

Organization

json
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Cogny AI",
  "url": "https://cogny.com",
  "logo": "https://cogny.com/images/logo.png",
  "sameAs": [
    "https://twitter.com/cognyai",
    "https://linkedin.com/company/cogny",
    "https://github.com/cognyai"
  ],
  "contactPoint": {
    "@type": "ContactPoint",
    "telephone": "+46-8-123-4567",
    "contactType": "customer service",
    "availableLanguage": ["English", "Swedish"]
  },
  "foundingDate": "2023",
  "numberOfEmployees": {
    "@type": "QuantitativeValue",
    "value": 15
  }
}

Required: name | Recommended: url, logo, sameAs, contactPoint Rich result: Knowledge panel

LocalBusiness

json
{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "name": "Nordic Coffee Roasters",
  "image": "https://example.com/photos/storefront.jpg",
  "url": "https://nordiccoffee.se",
  "telephone": "+46-8-765-4321",
  "priceRange": "$$",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "Drottninggatan 45",
    "addressLocality": "Stockholm",
    "addressRegion": "Stockholm",
    "postalCode": "111 21",
    "addressCountry": "SE"
  },
  "geo": {
    "@type": "GeoCoordinates",
    "latitude": 59.3293,
    "longitude": 18.0686
  },
  "openingHoursSpecification": [
    {
      "@type": "OpeningHoursSpecification",
      "dayOfWeek": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"],
      "opens": "07:00",
      "closes": "18:00"
    },
    {
      "@type": "OpeningHoursSpecification",
      "dayOfWeek": ["Saturday", "Sunday"],
      "opens": "09:00",
      "closes": "16:00"
    }
  ]
}

Required: name, address | Recommended: geo, openingHoursSpecification, telephone, priceRange, image Rich result: Local pack, knowledge panel with map/hours/phone

Product

json
{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Wireless Noise-Cancelling Headphones",
  "image": [
    "https://example.com/photos/headphones-front.jpg",
    "https://example.com/photos/headphones-side.jpg"
  ],
  "description": "Premium wireless headphones with active noise cancellation, 30-hour battery life, and multipoint Bluetooth connectivity.",
  "sku": "WH-1000XM5",
  "brand": {
    "@type": "Brand",
    "name": "AudioTech"
  },
  "offers": {
    "@type": "Offer",
    "url": "https://example.com/headphones-wh1000xm5",
    "priceCurrency": "USD",
    "price": "349.99",
    "priceValidUntil": "2025-12-31",
    "availability": "https://schema.org/InStock",
    "itemCondition": "https://schema.org/NewCondition",
    "seller": {
      "@type": "Organization",
      "name": "AudioTech Store"
    }
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.7",
    "bestRating": "5",
    "reviewCount": "2847"
  }
}

Required for rich results: name, image, offers (with price, priceCurrency, availability) Recommended: sku, brand, aggregateRating, description Rich result: Product snippet with price, availability, star rating

FAQPage

json
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is structured data?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Structured data is machine-readable markup added to HTML pages that helps search engines understand your content. It uses the Schema.org vocabulary and is typically implemented in JSON-LD format."
      }
    },
    {
      "@type": "Question",
      "name": "Does structured data improve SEO rankings?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Structured data does not directly affect rankings. However, it enables rich results that significantly improve click-through rates, which can indirectly improve performance through higher engagement signals."
      }
    }
  ]
}

Required: mainEntity array with Question items containing acceptedAnswer Rich result: None in Google Search any more. From September 2023 it was shown only for well-known, authoritative government and health sites; Google stopped showing it entirely on May 7, 2026 and removed the documentation in June 2026 (https://developers.google.com/search/updates). The markup is still valid Schema.org and other consumers may read it, but don't promise a rich result.

HowTo

json
{
  "@context": "https://schema.org",
  "@type": "HowTo",
  "name": "How to Implement JSON-LD Structured Data",
  "description": "A step-by-step guide to adding Schema.org JSON-LD structured data to your website.",
  "totalTime": "PT15M",
  "estimatedCost": {
    "@type": "MonetaryAmount",
    "currency": "USD",
    "value": "0"
  },
  "tool": [
    { "@type": "HowToTool", "name": "Text editor or CMS" },
    { "@type": "HowToTool", "name": "Google Rich Results Test" }
  ],
  "step": [
    {
      "@type": "HowToStep",
      "name": "Choose your schema type",
      "text": "Identify the primary content type of your page and look up the required properties at schema.org.",
      "url": "https://example.com/guide#step1",
      "image": "https://example.com/images/step1.png"
    },
    {
      "@type": "HowToStep",
      "name": "Write the JSON-LD block",
      "text": "Create a JSON-LD script block with @context, @type, and all required properties.",
      "url": "https://example.com/guide#step2",
      "image": "https://example.com/images/step2.png"
    },
    {
      "@type": "HowToStep",
      "name": "Insert into your page",
      "text": "Place the script tag in the head or body of your HTML document.",
      "url": "https://example.com/guide#step3",
      "image": "https://example.com/images/step3.png"
    },
    {
      "@type": "HowToStep",
      "name": "Validate with testing tools",
      "text": "Run your page through the Google Rich Results Test and Schema Markup Validator.",
      "url": "https://example.com/guide#step4",
      "image": "https://example.com/images/step4.png"
    }
  ]
}

Required: name, step (with text each) | Recommended: image per step, totalTime, tool Rich result: None. Google deprecated How-to rich results on September 13, 2023 (desktop and mobile) and removed the docs (https://developers.google.com/search/blog/2023/08/howto-faq-changes). Valid Schema.org, no Google SERP feature.

Article / BlogPosting

json
{
  "@context": "https://schema.org",
  "@type": "BlogPosting",
  "headline": "Complete Guide to Schema.org Structured Data",
  "description": "Learn how to implement structured data markup to earn rich results in Google Search.",
  "image": [
    "https://example.com/images/guide-16x9.jpg",
    "https://example.com/images/guide-4x3.jpg",
    "https://example.com/images/guide-1x1.jpg"
  ],
  "author": {
    "@type": "Person",
    "name": "Anna Lindqvist",
    "url": "https://example.com/authors/anna-lindqvist"
  },
  "publisher": {
    "@type": "Organization",
    "name": "Example Publishing",
    "logo": { "@type": "ImageObject", "url": "https://example.com/logo.png" }
  },
  "datePublished": "2025-01-15",
  "dateModified": "2025-02-10",
  "mainEntityOfPage": {
    "@type": "WebPage",
    "@id": "https://example.com/guides/structured-data"
  }
}

Use Article for news, BlogPosting for blogs, NewsArticle for Google News publishers.

Required: headline, image, datePublished, author Rich result: Article carousel, Top Stories (NewsArticle), author/date in results

BreadcrumbList

json
{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    { "@type": "ListItem", "position": 1, "name": "Home", "item": "https://example.com/" },
    { "@type": "ListItem", "position": 2, "name": "Docs", "item": "https://example.com/docs" },
    { "@type": "ListItem", "position": 3, "name": "Structured Data", "item": "https://example.com/docs/structured-data" }
  ]
}

Required: itemListElement with position, name, item Rich result: Breadcrumb trail replaces URL in search results

Review / AggregateRating

json
{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Cloud Analytics Platform",
  "review": [
    {
      "@type": "Review",
      "reviewRating": { "@type": "Rating", "ratingValue": "5", "bestRating": "5" },
      "author": { "@type": "Person", "name": "Erik Johansson" },
      "reviewBody": "Transformed our data pipeline. The BigQuery integration is seamless.",
      "datePublished": "2025-01-20"
    }
  ],
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.8",
    "bestRating": "5",
    "ratingCount": "312",
    "reviewCount": "189"
  }
}

Reviews must be nested inside the item they review — standalone Review markup without context will not generate rich results.

Required: ratingValue, bestRating, author (Review); ratingValue, ratingCount (AggregateRating) Rich result: Star rating snippet

Event

json
{
  "@context": "https://schema.org",
  "@type": "Event",
  "name": "Nordic Growth Marketing Summit 2025",
  "description": "Two-day conference on performance marketing and AI-driven analytics.",
  "startDate": "2025-09-15T09:00:00+02:00",
  "endDate": "2025-09-16T17:00:00+02:00",
  "eventStatus": "https://schema.org/EventScheduled",
  "eventAttendanceMode": "https://schema.org/OfflineEventAttendanceMode",
  "location": {
    "@type": "Place",
    "name": "Stockholm Waterfront Congress Centre",
    "address": {
      "@type": "PostalAddress",
      "streetAddress": "Nils Ericsons Plan 4",
      "addressLocality": "Stockholm",
      "postalCode": "111 64",
      "addressCountry": "SE"
    }
  },
  "performer": { "@type": "Organization", "name": "Cogny AI" },
  "offers": {
    "@type": "Offer",
    "url": "https://example.com/tickets",
    "price": "4999",
    "priceCurrency": "SEK",
    "availability": "https://schema.org/InStock",
    "validFrom": "2025-03-01T00:00:00+01:00"
  },
  "organizer": { "@type": "Organization", "name": "Growth Hackers Stockholm", "url": "https://growthhackers.se" },
  "image": "https://example.com/images/summit-2025.jpg"
}

Required: name, startDate, location | Recommended: endDate, offers, performer, eventStatus, image Rich result: Event listing with date/location/ticket; event pack in SERP

VideoObject

json
{
  "@context": "https://schema.org",
  "@type": "VideoObject",
  "name": "How to Set Up GA4 BigQuery Export",
  "description": "Step-by-step tutorial for connecting GA4 to BigQuery.",
  "thumbnailUrl": "https://example.com/thumbnails/ga4-setup.jpg",
  "uploadDate": "2025-01-10",
  "duration": "PT12M30S",
  "contentUrl": "https://example.com/videos/ga4-setup.mp4",
  "embedUrl": "https://youtube.com/embed/abc123",
  "interactionStatistic": {
    "@type": "InteractionCounter",
    "interactionType": { "@type": "WatchAction" },
    "userInteractionCount": 15420
  }
}

Required: name, thumbnailUrl, uploadDate | Recommended: description, duration, contentUrl or embedUrl Rich result: Video carousel, video thumbnail in search results

SoftwareApplication

json
{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "Cogny Analytics Platform",
  "operatingSystem": "Web",
  "applicationCategory": "BusinessApplication",
  "description": "AI-powered analytics platform for automated growth insights.",
  "offers": { "@type": "Offer", "price": "99", "priceCurrency": "USD" },
  "aggregateRating": { "@type": "AggregateRating", "ratingValue": "4.8", "ratingCount": "156" },
  "screenshot": "https://example.com/images/dashboard.png"
}

Required: name, offers (with price, priceCurrency) | Recommended: operatingSystem, applicationCategory, aggregateRating Rich result: Software snippet with rating and price

Course

json
{
  "@context": "https://schema.org",
  "@type": "Course",
  "name": "Advanced BigQuery for Marketing Analytics",
  "description": "Learn to write efficient BigQuery SQL for GA4 data, build attribution models, and create automated reporting.",
  "provider": { "@type": "Organization", "name": "Cogny Academy", "sameAs": "https://cogny.com/academy" },
  "courseCode": "BQ-301",
  "hasCourseInstance": {
    "@type": "CourseInstance",
    "courseMode": "online",
    "courseSchedule": {
      "@type": "Schedule",
      "repeatFrequency": "P1W",
      "startDate": "2025-03-01",
      "endDate": "2025-04-15"
    }
  },
  "offers": { "@type": "Offer", "price": "499", "priceCurrency": "USD", "category": "Paid" }
}

Required: name, description, provider | Recommended: offers, hasCourseInstance Rich result: Course listing with provider and enrollment info

JobPosting

json
{
  "@context": "https://schema.org",
  "@type": "JobPosting",
  "title": "Senior Growth Engineer",
  "description": "Build and optimize marketing analytics infrastructure including BigQuery pipelines, A/B testing, and automated reporting.",
  "datePosted": "2025-02-01",
  "validThrough": "2025-04-01T23:59:59+01:00",
  "employmentType": "FULL_TIME",
  "hiringOrganization": {
    "@type": "Organization",
    "name": "Cogny AI",
    "sameAs": "https://cogny.com",
    "logo": "https://cogny.com/images/logo.png"
  },
  "jobLocation": {
    "@type": "Place",
    "address": {
      "@type": "PostalAddress",
      "addressLocality": "Stockholm",
      "addressRegion": "Stockholm",
      "addressCountry": "SE"
    }
  },
  "jobLocationType": "TELECOMMUTE",
  "baseSalary": {
    "@type": "MonetaryAmount",
    "currency": "SEK",
    "value": { "@type": "QuantitativeValue", "minValue": 55000, "maxValue": 75000, "unitText": "MONTH" }
  },
  "applicantLocationRequirements": { "@type": "Country", "name": "Sweden" }
}

Required: title, description, datePosted, hiringOrganization, jobLocation Recommended: validThrough, employmentType, baseSalary, jobLocationType Rich result: Google Jobs listing with salary, location, apply button

Testing and Validation

Google Rich Results Test

URL: https://search.google.com/test/rich-results

Test individual pages or code snippets for rich result eligibility. Shows detected types, validation errors, and warnings. It runs in a browser (no public API, and WebFetch can't drive it), so hand the user the link; for an automated check use the curl audit above.

Schema Markup Validator

URL: https://validator.schema.org

Validates against the full Schema.org specification — catches structural errors the Rich Results Test may miss.

Google Search Console Rich Results Report

Location: Search Console > Enhancements > [specific rich result type]

Aggregate data across your site: valid pages, error counts, specific error types. Updated daily.

Common Validation Errors

Error	Cause	Fix
`Missing field "image"`	Product/Article missing image	Add `image` with valid crawlable URL
`Invalid URL in field "url"`	Relative URL	Use fully qualified URLs (`https://...`)
`Missing field "author"`	Article/Review missing author	Add `author` as Person or Organization with `name`
`Invalid value in field "price"`	Currency symbol in price	Use numeric value only (`"349.99"` not `"$349.99"`)
`Invalid enum for "availability"`	Plain text instead of URL	Use `https://schema.org/InStock`, not `"In Stock"`
`Array expected, single value`	Single image instead of array	Wrap in array: `"image": ["https://..."]`
`datePublished is in the future`	Date set ahead of publish	Set to actual publication date

Best Practices

One Primary Schema Type per Page

Match the primary schema type to the page purpose. Product pages use Product, blog posts use BlogPosting, FAQ pages may use FAQPage (no Google rich result). Combine with BreadcrumbList as a complementary type.

Nesting vs. @graph

Nest when there is a parent-child relationship (Product > Offer). Use @graph for independent entities on the same page:

json
{
  "@context": "https://schema.org",
  "@graph": [
    { "@type": "BreadcrumbList", "itemListElement": [...] },
    { "@type": "Product", "name": "Widget", "offers": {...} }
  ]
}

Required vs. Recommended Properties

Required properties must be present for the rich result to appear. Recommended properties improve quality and appearance. Always include both.

Avoiding Spammy Markup

Do not fabricate reviews or ratings
Schema properties must match visible page content
Do not add schema for hidden content
Do not mismatch schema type and page purpose
Self-serving reviews without genuine third-party data trigger manual actions

Google manual actions for structured data spam can remove all rich results from your entire domain.

Keeping Schema in Sync

Generate structured data from the same data source as page content. Include schema updates in your CMS publishing workflow. Audit quarterly or after major site changes.

Rich Results Eligibility

Schema Type	Rich Result	SERP Appearance
`Product`	Product snippet	Price, availability, stars
`FAQPage`	None (retired)	Gov/health only from Sept 2023; not shown at all from May 7, 2026
`HowTo`	None (retired)	Deprecated Sept 13, 2023 on desktop and mobile
`Article` / `BlogPosting`	Article result	Author, date, thumbnail
`NewsArticle`	Top Stories	Carousel at top of results
`BreadcrumbList`	Breadcrumb trail	Replaces URL with nav path
`Review` / `AggregateRating`	Review snippet	Star rating below listing (not for self-serving reviews on your own `Organization`/`LocalBusiness`)
`Event`	Event listing	Date, location, tickets
`VideoObject`	Video result	Thumbnail, duration
`LocalBusiness`	Local pack	Map, hours, phone
`JobPosting`	Google Jobs	Salary, location, apply
`SoftwareApplication`	Software result	Rating, price
`Course`	Course listing	Provider, enrollment
`Organization`	Knowledge panel	Logo, social links

Implementation Patterns

Static HTML

html
<head>
  <script type="application/ld+json">
  { "@context": "https://schema.org", "@type": "Product", ... }
  </script>
</head>

Next.js (App Router)

tsx
export default function ProductPage({ product }) {
  const jsonLd = {
    "@context": "https://schema.org",
    "@type": "Product",
    name: product.name,
    image: product.images,
    offers: {
      "@type": "Offer",
      price: product.price,
      priceCurrency: product.currency,
      availability: product.inStock
        ? "https://schema.org/InStock"
        : "https://schema.org/OutOfStock",
    },
  };
  return (
    <>
      <script
        type="application/ld+json"
        dangerouslySetInnerHTML={{ __html: JSON.stringify(jsonLd) }}
      />
      {/* content */}
    </>
  );
}

WordPress

Use Yoast SEO, Rank Math, or Schema Pro plugins. For custom implementation:

php
add_action('wp_head', function() {
    if (is_singular('product')) {
        $product = get_post();
        $price = get_post_meta($product->ID, '_price', true);
        $schema = [
            '@context' => 'https://schema.org',
            '@type' => 'Product',
            'name' => $product->post_title,
            'offers' => [
                '@type' => 'Offer',
                'price' => $price,
                'priceCurrency' => 'USD',
                'availability' => 'https://schema.org/InStock',
            ],
        ];
        echo '<script type="application/ld+json">' . json_encode($schema) . '</script>';
    }
});

Dynamic CMS Pattern

typescript
function generateProductSchema(cmsData: CMSProduct): object {
  return {
    "@context": "https://schema.org",
    "@type": "Product",
    name: cmsData.title,
    image: cmsData.media.map(m => m.url),
    offers: {
      "@type": "Offer",
      price: cmsData.variants[0].price.toString(),
      priceCurrency: cmsData.currency,
      availability: cmsData.inStock
        ? "https://schema.org/InStock"
        : "https://schema.org/OutOfStock",
    },
  };
}

Key principle: generate structured data from the same data source that populates the page, never hardcode separately.

Resources

Schema.org Full Vocabulary: https://schema.org/docs/full.html
Google Rich Results Gallery: https://developers.google.com/search/docs/appearance/structured-data/search-gallery
Google Rich Results Test: https://search.google.com/test/rich-results
Schema Markup Validator: https://validator.schema.org
Full Cogny Docs: https://cogny.com/docs/structured-data-reference

Publisher	cognyai
Repository	`claude-code-marketing-skills`
Skill name	`structured-data`
Stars	111
Forks	15
Bundled files	Instructions only
Links	Skill source Repository Homepage

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Schema.org Structured Data Reference

Usage

Instructions

Works with

Audit a live page (/structured-data audit <url>)

What Structured Data Does

Formats

JSON-LD (Recommended)

Microdata

RDFa

Schema Types with JSON-LD Examples

Organization

LocalBusiness

Product

FAQPage

HowTo

Article / BlogPosting

BreadcrumbList

Review / AggregateRating

Event

VideoObject

SoftwareApplication

Course

JobPosting

Testing and Validation

Google Rich Results Test

Schema Markup Validator

Google Search Console Rich Results Report

Common Validation Errors

Best Practices

One Primary Schema Type per Page

Nesting vs. @graph

Required vs. Recommended Properties

Avoiding Spammy Markup

Keeping Schema in Sync

Rich Results Eligibility

Implementation Patterns

Static HTML

Next.js (App Router)

WordPress

Dynamic CMS Pattern

Resources

Frequently asked questions

Related AI Skills

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Audit a live page (`/structured-data audit <url>`)