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Schema

CommunityPopular
coreyhaines31
schema

When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," "breadcrumb schema," "Google rich results," "knowledge panel," "star ratings in search," or "add structured data." Use this whenever someone wants their pages to show enhanced results in Google. For broader SEO issues, see seo-audit. For AI search optimization, see ai-seo.

Overview

Publishercoreyhaines31
Repositorymarketingskills
Skill nameschema
Stars
50.7K
Forks
7.7K
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by coreyhaines31 on GitHub. Read the source before you install it.

Installation

Install the Schema AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/coreyhaines31/marketingskills.git /tmp/marketingskills
mkdir -p .claude/skills
cp -r /tmp/marketingskills/skills/schema .claude/skills/schema
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Schema in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Schema on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Schema is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, 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

TypeUse ForRequired Properties
OrganizationCompany homepage/aboutname, url
WebSiteHomepage (search box)name, url
ArticleBlog posts, newsheadline, image, datePublished, author
ProductProduct pagesname, image, offers
SoftwareApplicationSaaS/app pagesname, offers
FAQPageFAQ contentmainEntity (Q&A array)
HowToTutorialsname, step
BreadcrumbListAny page with breadcrumbsitemListElement
LocalBusinessLocal business pagesname, address
EventEvents, webinarsname, 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:

json
{
  "@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

json
// 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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Schema AI skill do?

When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," "breadcrumb schema," "Google rich results," "knowledge panel," "star ratings in search," or "add structured data." Use this whenever someone wants their pages to show enhanced results in Google. For broader SEO issues, see seo-audit. For AI search optimization, see ai-seo.

Why use Schema on TypingMind?

Because you install it once and use it with any model. Schema 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 Schema in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/coreyhaines31/marketingskills/tree/main/skills/schema. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Schema?

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 Schema?

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

Is the Schema AI skill free?

Yes. It is published on GitHub by coreyhaines31 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

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.

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