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Custom prompt shortcut / SEO

/schema — ChatGPT Prompt Guide

Explore the /schema custom ChatGPT prompt shortcut with a practical template, examples, and review steps. Learn how to refine outputs for your workflow.

What does /schema do?

Purpose: Practical case study: Plan structured data for a tutorial.

This is a custom prompt convention, not a built-in or official ChatGPT slash command. Entering the slash text alone does not guarantee that ChatGPT will invoke a special tool. Use the complete structured prompt below or configure your own app to interpret this shortcut.

Key decision for this workflow

Use /schema when the task is mark up a published how-to guide with valid structured data; specify the evidence needed to accept the result.

Copy-ready task brief

/schema Objective: Mark up a published how-to guide with valid structured data Inputs: Visible page title, author attribution, date and actual on-page steps Deliverable: Minimal JSON-LD reflecting the real article and appropriate schema types

Reusable prompt template

/schema Objective: Mark up a published how-to guide with valid structured data Available materials: Visible page title, author attribution, date and actual on-page steps Required output: Minimal JSON-LD reflecting the real article and appropriate schema types Acceptance test: Validate syntax and compare every property against visible page content Boundary: Valid JSON-LD does not guarantee rich-result eligibility Return the requested deliverable first, then a brief verification checklist and any unresolved questions.

How to use this shortcut

  1. Collect the source inputs: Visible page title, author attribution, date and actual on-page steps
  2. Run /schema with the copy-ready task brief above.
  3. Request the concrete output: Minimal JSON-LD reflecting the real article and appropriate schema types
  4. Check the result: Validate syntax and compare every property against visible page content

Quality checks and limitations

Acceptance criteria: Validate syntax and compare every property against visible page content Limitation: Valid JSON-LD does not guarantee rich-result eligibility

Related tools and learning

Continue with the 35 prompt generators, the technical AI Guides, and the Image Guides for deeper examples.

/seo/keywordresearch/contentcluster/topicalauthority/lowpoly/cyberpunk

Worked example and expected output

Input materials: Visible page title, author attribution, date and actual on-page steps

Requested result: Minimal JSON-LD reflecting the real article and appropriate schema types

Acceptance test: Validate syntax and compare every property against visible page content

Practical case study: Plan structured data for a tutorial

Starting brief: Page: original how-to article about adjusting a telescope finder; visible numbered steps.

Expected deliverable: Identify appropriate structured-data types, required properties and JSON-LD validation steps.

Quality gate: Markup must reflect visible content and does not guarantee rich results.

/schema
Task: Plan structured data for a tutorial.
Input: Page: original how-to article about adjusting a telescope finder; visible numbered steps.
Deliverable: Identify appropriate structured-data types, required properties and JSON-LD validation steps.
Review: Markup must reflect visible content and does not guarantee rich results.

Worked workflow: Mark up a published how-to guide with valid structured data

Practical scenario: Mark up a published how-to guide with valid structured data

Inputs to provide: Visible page title, author attribution, date and actual on-page steps

Requested deliverable: Minimal JSON-LD reflecting the real article and appropriate schema types

How to verify the result: Validate syntax and compare every property against visible page content

Important limitation: Valid JSON-LD does not guarantee rich-result eligibility

Frequently asked questions

Is /schema an official ChatGPT command? No. It is a reusable custom shorthand from this catalog. Does it work without a plugin? You can copy the full prompt into an assistant; automatic slash-command routing requires application logic. Can the output be trusted without review? No. Review accuracy, safety, and suitability before use.