Schema.org Structured Data Generator

Automatically generates Schema.org structured data in JSON format for any website URL, making it easier for search engines to understand and index your website content. Ideal for improving SEO and web visibility by extracting site content and converting it into rich structured metadata.

How the AI Flow works - Schema.org Structured Data Generator

Flows

How the AI Flow works

User Provides Website URL.
Collects a website URL from the user as input.
Retrieve Content from URL.
Fetches and extracts the textual content from the provided website URL.
Prepare Schema.org Prompt.
Formats the extracted content into a prompt template designed to generate structured Schema.org data.
Generate Structured Data.
Uses an AI model to generate Schema.org structured data in JSON format based on the prompt and website content.
Display Generated Schema.
Outputs the generated Schema.org JSON for the user to copy or use on their website.

Prompts used in this flow

Below is a complete list of all prompts used in this flow to achieve its functionality. Prompts are the instructions given to the AI model to generate responses or perform actions. They guide the AI in understanding user intent and generating relevant outputs.

Prompt

Creates a prompt template for LLM to generate Schema.org structured data based on extracted website information.

                You are a skilled programmer tasked to create Schema.org structured data based on website information from {context}. Use "about" Schema attribute to tell what the article is about and "sameAs" to point to the most relevant and authoritative website. Use "mentions" Schema attribute for other related keywords mentioned in the article. For listicles add itemlist and listitem for item from the list.
 ---SCHEMA.ORG---
---
            

Components used in this flow

Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.

ChatInput

The Chat Input component in FlowHunt initiates user interactions by capturing messages from the Playground. It serves as the starting point for flows, enabling the workflow to process both text and file-based inputs.

URL Retriever

Unlock web content in your workflows with the URL Retriever component. Effortlessly extract and process the text and metadata from any list of URLs—including web articles, documents, and more. Supports advanced options like OCR for images, selective metadata extraction, and customizable caching, making it ideal for building knowledge-rich AI flows and automations.

Prompt Component in FlowHunt

Learn how FlowHunt's Prompt component lets you define your AI bot’s role and behavior, ensuring relevant, personalized responses. Customize prompts and templates for effective, context-aware chatbot flows.

Generator

Explore the Generator component in FlowHunt—powerful AI-driven text generation using your chosen LLM model. Effortlessly create dynamic chatbot responses by combining prompts, optional system instructions, and even images as input, making it a core tool for building intelligent, conversational workflows.

Chat Output

Discover the Chat Output component in FlowHunt—finalize chatbot responses with flexible, multi-part outputs. Essential for seamless flow completion and creating advanced, interactive AI chatbots.

Message Widget

The Message Widget component displays custom messages within your workflow. Ideal for welcoming users, providing instructions, or showing any important information, it supports Markdown formatting and can be set to appear only once per session.

Chat Opened Trigger

The Chat Opened Trigger component detects when a chat session starts, enabling workflows to respond instantly as soon as a user opens the chat. It initiates flows with the initial chat message, making it essential for building responsive, interactive chatbots.

Flow description

Purpose and benefits

Overview

This workflow, titled “Schema.org Generator”, is designed to automate the process of creating Schema.org structured data in JSON format for any given website URL. Schema.org markup helps search engines better understand your website’s content, which can improve SEO and how your pages are displayed in search results.

The workflow is currently set up to generate the following schema attributes: about, sameAs, mentions, listItem, and ItemList. However, you can easily customize which schema elements are generated by modifying the prompt.


Step-by-Step Flow

1. User Interaction and Welcome Message

  • When a user opens the chat interface, a welcome message is displayed.
  • The message explains the tool’s purpose and instructs the user to provide a URL.

2. User Input

  • The user enters (or pastes) the URL of a webpage for which they want to generate Schema.org structured data.

3. Retrieving Website Content

  • The workflow fetches the content of the provided URL using a URL Retriever component.
  • This component extracts the main text or document content of the page to be analyzed further.

4. Building the Prompt

  • The workflow uses a Prompt Template component, which:
    • Receives the website content (as “context”).
    • Receives the original user input (the URL).
    • Fills a predefined prompt instructing an AI model to generate Schema.org JSON based on the content.
    • The prompt specifically guides the model to:
      • Use "about" to describe the article’s main topic.
      • Use "sameAs" for the most authoritative related website.
      • Use "mentions" for other related entities or keywords.
      • For list articles, create "ItemList" and "listItem" entries.

5. AI-Powered Generation

  • The constructed prompt is fed into a Generator component, which uses a language model (LLM) to produce the requested Schema.org JSON.

6. Output Display

  • The generated Schema.org JSON is displayed to the user in the chat interface.

Workflow Structure

StepComponentPurpose
1Chat Opened Trigger & Message WidgetGreets the user and explains workflow usage
2Chat InputReceives the URL from the user
3URL RetrieverFetches and parses content from the provided URL
4Prompt TemplateAssembles the AI prompt with context and instructions
5GeneratorUses LLM to generate Schema.org JSON from the prompt
6Chat OutputDisplays generated Schema.org JSON to the user

Key Features & Benefits

  • Automation: Eliminates manual creation of Schema.org markup for each webpage, saving time and reducing errors.
  • Scalability: Can be used repeatedly for any number of URLs, supporting bulk or batch processing.
  • Customization: Easily adaptable to generate different Schema.org attributes by editing the prompt.
  • SEO Enhancement: Improves visibility and clarity for search engines, potentially boosting search rankings and rich results.
  • User-Friendly: Simple chat-based interface lowers the barrier for non-technical users.

Use Cases

  • Website owners and SEOs who want to quickly generate structured data for their articles, product pages, or listicles.
  • Agencies managing multiple client websites needing standardized, consistent schema markup.
  • Developers integrating Schema.org automation into their content pipelines or CMS workflows.

Example User Flow

  1. Visit the tool: User opens the chat and is greeted with instructions.
  2. Enter URL: User inputs the URL of the target webpage.
  3. Receive Schema.org JSON: The tool returns a ready-to-use JSON snippet tailored to the page content, which can be added to the website.

By automating Schema.org JSON generation, this workflow helps you scale your structured data implementation, ensuring your content is easily understood by search engines and enhancing your site’s presence in search results.

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