Structured Data for GEO
Recommend the schema types that help machines understand your page — without over-promising citations
What This Prompt Does
Structured data (JSON-LD) is a direct line of communication between your page and any machine that reads it. This prompt reads your content and recommends only the schema types the page can actually support — explaining why each one helps AI systems and which types would be misleading.
When to Use It
- •Rolling out schema on a new site or section
- •Replacing over-aggressive or incorrect existing schema
- •Preparing a page for Wikipedia-style verification by AI
- •Ensuring brand and entity data is machine-readable, not just visually present
The Prompt Template
Act as a technical content and GEO specialist. Your goal is to recommend structured data that would make this page easier for machines to understand. Context: - Business type: [BUSINESS TYPE] - Page type: [PAGE TYPE] - Page content: [PASTE PAGE CONTENT] Task: Identify: 1. which schema types fit the page 2. why they help with machine understanding 3. what key properties should be included 4. what schema should not be used because it is unsupported Process: 1. Review the visible content. 2. Match the content to appropriate schema types. 3. Explain the value of each schema type in plain English. 4. Flag any markup that would be misleading. Constraints: - Use simple language. - Only recommend schema supported by visible content. - Do not claim structured data guarantees AI citations. - Keep it practical. - Favor clearer facts, direct answers, and useful specifics over polished marketing language. Output format: Return a table with these columns: - Schema Type - Use It: Yes or No - Why It Helps - Important Properties
How the Prompt Is Structured
"Only Schema Supported by Visible Content"
Google and other validators penalize schema that makes claims the page doesn't show. The constraint keeps the output within the bounds of what your page actually says.
"Do Not Claim Structured Data Guarantees AI Citations"
Structured data helps — it doesn't guarantee. The constraint keeps the recommendations honest and the expectations realistic.
"Use It: Yes or No"
A binary verdict. Every schema type gets a clear decision rather than "maybe" hedging that doesn't help you act.
Important Properties, Not All Properties
Schema types often have 50+ optional fields. Asking for the "important properties" produces a minimum viable implementation rather than a dump.
Example Output
| Schema Type | Use It | Why It Helps | Important Properties |
|---|---|---|---|
| Organization | Yes | Defines the brand as a verifiable entity for machines. | name, url, logo, sameAs (LinkedIn, GBP, Wikipedia) |
| LocalBusiness | Yes | Anchors the business to a physical location and service area. | name, address, telephone, areaServed, openingHours |
| FAQPage | Yes | Structures Q&A in a format AI systems can lift directly. | mainEntity (Question / Answer pairs) |
| Review / AggregateRating | No | No visible reviews on the page yet — adding the markup would violate visible-content rules. | — |
Tips for Better Results
Use sameAs Aggressively
`sameAs` links your Organization to LinkedIn, Google Business, Wikipedia, and social profiles — one of the most useful GEO properties.
Validate Before Publishing
Run every JSON-LD through Schema.org's validator and Google's Rich Results Test before deploying.
Add Content First, Then Markup
If the prompt tells you "no" for a schema type, add the visible content first. Then re-run and add the markup.
Ask for the JSON-LD Next
Once you have the list of schema types, a follow-up "generate the JSON-LD for these types" produces the code you can paste into the page.
Give Machines a Map, Not a Maze
We design structured-data implementations that make pages machine-readable without triggering misleading-markup penalties.