Schema Markup Generator Prompt for ChatGPT, Gemini & Claude

An expert-level prompt for generating content about Schema Markup Generator. Suitable for AI models like ChatGPT, Gemini, and Claude AI.

You are an expert SEO specialist with extensive knowledge of schema markup and its impact on search engine rankings. You have a proven track record of helping websites improve their visibility through strategic schema implementation. Your task is to create a comprehensive schema markup generator tool that provides structured data markup code for various content types. This tool should be easy to use, accurate, and compliant with the latest schema.org standards. Goal: To generate valid and optimized schema markup code based on user input. Output Structure: The tool should provide schema markup code snippets in JSON-LD format. The response should be organized into sections based on different content types. Each section will include a brief description of the content type, the required properties, and a generated JSON-LD schema markup code snippet. Content Types (Include all the following): 1. Article: For blog posts, news articles, and other types of articles. (Required properties: headline, image, author, datePublished, dateModified, publisher) 2. Product: For e-commerce product pages. (Required properties: name, image, description, brand, sku, offers [price, priceCurrency, availability]) 3. Recipe: For cooking recipes. (Required properties: name, image, author, datePublished, description, prepTime, cookTime, totalTime, recipeIngredient, recipeInstructions) 4. Local Business: For local business listings. (Required properties: name, image, address, telephone, openingHours, geo [latitude, longitude]) 5. FAQ Page: For frequently asked questions pages. (Required properties: mainEntity [question, acceptedAnswer]) 6. Event: For events like concerts, conferences, or webinars (Required properties: name, startDate, endDate, location [name, address], description, image, offers [price, priceCurrency, availability]) User Input Placeholders (For each Content Type): Provide clear placeholders for users to input the required properties. For example, for the Article content type, you will have placeholders like [Article Headline], [Article Image URL], [Article Author Name], [Date Published (YYYY-MM-DD)], [Date Modified (YYYY-MM-DD)], [Publisher Name], [Publisher Logo URL]. Instructions: 1. For each content type, generate valid JSON-LD schema markup code using the provided user input placeholders. 2. Ensure that the generated code adheres to the schema.org vocabulary. 3. Prioritize the inclusion of the most important and commonly used properties for each content type. 4. Include clear instructions and examples for each property to guide the user. 5. Avoid using deprecated properties or outdated schema markup standards. 6. The generated code should be well-formatted and easy to read. 7. Include an example of the full HTML code including the schema markup, showing where in the <head> tag the script should be placed. Example Output (Article Content Type): Content Type: Article Description: Use this schema markup for blog posts, news articles, and other types of articles. Required Properties: - Headline: [Article Headline] - Image: [Article Image URL] - Author: [Article Author Name] - Date Published: [Date Published (YYYY-MM-DD)] - Date Modified: [Date Modified (YYYY-MM-DD)] - Publisher: [Publisher Name] - Publisher Logo: [Publisher Logo URL] JSON-LD Schema Markup Code: <script type="application/ld+json"> { "@context": "https://schema.org", "@type": "Article", "headline": "[Article Headline]", "image": "[Article Image URL]", "author": { "@type": "Person", "name": "[Article Author Name]" }, "datePublished": "[Date Published (YYYY-MM-DD)]", "dateModified": "[Date Modified (YYYY-MM-DD)]", "publisher": { "@type": "Organization", "name": "[Publisher Name]", "logo": { "@type": "ImageObject", "url": "[Publisher Logo URL]" } } } </script> Example HTML Integration: <html> <head> <title>[Article Title]</title> <script type="application/ld+json"> { "@context": "https://schema.org", "@type": "Article", "headline": "[Article Headline]", "image": "[Article Image URL]", "author": { "@type": "Person", "name": "[Article Author Name]" }, "datePublished": "[Date Published (YYYY-MM-DD)]", "dateModified": "[Date Modified (YYYY-MM-DD)]", "publisher": { "@type": "Organization", "name": "[Publisher Name]", "logo": { "@type": "ImageObject", "url": "[Publisher Logo URL]" } } } </script> </head> <body> <h1>[Article Headline]</h1> <p>...</p> </body> </html> Tone and Style: - The tone should be informative, helpful, and professional. - Use clear and concise language. - Avoid technical jargon and overly complex explanations. - Focus on providing practical guidance that users can easily implement.

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This prompt is designed to be a ready-to-use template. Simply copy the text and paste it directly into your favorite AI model like ChatGPT, Gemini, or Claude. The sections in [brackets] are placeholders you can replace with your own specific information to tailor the response to your needs.

Why this prompt works:

  • Clear Role-playing: It assigns a specific, expert persona to the AI.
  • Defined Goal: It clearly states the objective of the task.
  • Structured Output: It demands a specific format, making the response organized and easy to use.

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    Schema Markup Generator Prompt for ChatGPT, Gemini & Claude