Schema markup: a step-by-step method and prompt

Schema markup is structured data, usually written as JSON-LD, that tells search engines exactly what a page is about: an article, a product, an organization, a how-to or a set of FAQs. It makes pages eligible for rich results and gives search engines and AI assistants unambiguous facts about your business.

What it is

Schema uses the shared vocabulary at schema.org. You add a <script type="application/ld+json"> block to the page with a type and its properties. For example, an Article has a headline, author, datePublished and image. A Product has a name, offers and price.

Google's structured data guidelines list which types can produce rich results and which properties are required. The key rule: markup must describe content that is visible on the page.

When to use it

• You publish articles, guides or docs and want accurate dates and authors shown.
• You sell products and want price and availability in results.
• You have a real FAQ section on a page.
• You want search engines to connect your brand, logo and social profiles.
• You are improving how AI assistants describe your company.

Step-by-step method

1. Map templates to types. List your page templates. Typical pairs: home to Organization and WebSite, blog post to Article or BlogPosting, product to Product, docs to TechArticle, contact to LocalBusiness if you have a physical location.
2. List required and recommended properties. For each type, read the matching Google guide and note required fields. Missing required fields block rich results.
3. Pull values from the page, not from memory. Headline, dates, prices and FAQ answers should come from the same data that renders the page, so they never drift apart.
4. Generate the JSON-LD. Write it by hand or use our schema markup generator to build and preview it. Add a BreadcrumbList on pages with breadcrumbs.
5. Add it to the template. Place the script in the page head or body. In frameworks, render it server-side so it is present in the initial HTML.
6. Validate. Test a live URL in the Rich Results Test and the Schema Markup Validator. Fix errors first, warnings second.
7. Monitor in Search Console. Check the Enhancements reports for new errors after deploys.

Ready-to-use prompt

You are a structured data specialist. Write JSON-LD for this page.

Page type: [ARTICLE / PRODUCT / FAQ / HOWTO / ORGANIZATION / LOCALBUSINESS]
Page URL: [URL]
Visible page content (paste the main text, headings, prices, FAQs, author, dates): [PASTE]
Organization details: name [NAME], logo URL [URL], social profiles [URLS]

Rules:
- Use only values that appear in the content I pasted. If a required property is missing, list it under "Missing" instead of inventing it.
- Use schema.org types and Google's required properties for rich results.
- Add a BreadcrumbList if I give you breadcrumb items: [ITEMS OR NONE].
- Output one valid JSON-LD script block, then a short list of properties I should double-check.

Checklist

• Every template mapped to a schema type
• Required properties present for each type
• Values pulled from the same source as the visible page
• No markup for content that is not on the page
• BreadcrumbList on pages with breadcrumbs
• JSON-LD rendered server-side in the initial HTML
• Rich Results Test passes with no errors
• Search Console Enhancements reports checked after deploys

How Thig automates it

The Coding agent adds or fixes JSON-LD in your codebase and opens a pull request you review. The Writer agent includes Article and FAQ schema with every article it prepares for publishing. Pair this with the technical SEO skill for the rest of the foundation.