How to use the Schema Markup Generator.
Structured data should describe visible, accurate page content. Required facts must come from the page or user; a schema type does not create rich-result eligibility.
Make the workflow fit your task.
Choose a schema type that matches the visible content and map each supplied fact to a supported property. Generate parseable JSON-LD, then compare the values with the page and the consumer's requirements.
- What you provide
- Page facts and requested supported schema type.
- What you get
- JSON-LD for types beyond existing product and FAQ pages.
See the input and the result.
Illustrative input and output · a teaching example, not a live WebAct run
Example input
Describe the visible organizer Example Workshop, URL https://example.com/, as Organization JSON-LD. No address, ratings or social profiles are supplied.
Completed example
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Example Workshop",
"url": "https://example.com/"
}
Only the supplied organization facts are included. Validate syntax and the requirements of the intended consumer before publication.Load this input into the prompt, then copy it to WebAct to try the task. Your result may differ from the illustration.
Decisions and troubleshooting.
Does valid JSON-LD guarantee a special search appearance?
No. Syntax, content accuracy and feature eligibility are separate checks. Markup should describe the page even when no special display appears.
Why does the draft include facts absent from the page?
Remove unsupported properties or supply and publish the missing facts. A schema example should not become invented evidence.
Reference for this workflow.
Try it with your own source.
Replace the example with your material in the task prompt. Keep the requirements you need, then copy the task into WebAct.
Customize and copy the task ↑