FAQ Generator with Schema.org Markup

Generate SEO-friendly FAQ sections from any website URL and automatically format the FAQs in Schema.org markup to enhance search engine visibility.

Flows

How the AI Flow works

User Opens Chat.: Detects when the chat is opened and displays a welcome message.
User Provides Website URL.: Collects the URL input from the user through the chat interface.
Retrieve Website Content.: Fetches and processes the content from the provided website URL.
Generate FAQ and Schema.org Markup.: Uses an AI agent to create relevant FAQ questions and answers from the website content, then formats them in Schema.org markup.
Display FAQ Output.: Presents the generated FAQs and Schema.org code to the user in the chat.

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.

FAQ Generation Agent

Agent that generates FAQ questions and answers from a website URL and outputs Schema.org code for them. The core LLM prompt for the workflow.

                You are tasked with generating FAQ questions for websites. You will create Questions and Answers from input which is a URL and generate a Schema.org for those FAQ questions.

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.

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.

See Chat Opened Trigger

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.

See Message Widget

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.

See Chat Output

Chat History Component

The Chat History component in FlowHunt enables chatbots to remember previous messages, ensuring coherent conversations and improved customer experience while optimizing memory and token usage.

See Chat History Component

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.

See ChatInput

Tool Calling Agent

Explore the Tool Calling Agent in FlowHunt—an advanced workflow component that enables AI agents to intelligently select and use external tools to answer complex queries. Perfect for building smart AI solutions that require dynamic tool usage, iterative reasoning, and integration with multiple resources.

See Tool Calling Agent

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.

See URL Retriever

Flow description

Purpose and benefits

This workflow is designed to automate the creation of FAQ sections for any website by extracting content from a user-provided URL, generating relevant questions and answers, and formatting them using Schema.org structured data (in JSON-LD format). This structure helps search engines better understand the context of your webpage, potentially improving SEO and search result appearance.

Step-by-Step Workflow Breakdown

1. User Initiation and Welcome Message

Chat Opened Trigger: The process begins when a user starts a chat session.
Message Widget: Immediately, the user is greeted with a welcome message, explaining that they can input a URL to generate FAQs and receive Schema.org code for SEO benefits.
Chat Output: This message is displayed in the user interface.

2. User Input and Data Collection

Chat Input: The user enters the desired website URL into the chat interface.
Chat History: The system keeps track of the chat history, useful for context if multiple turns are needed.

3. Content Retrieval

URL Retriever: The workflow fetches and processes the content from the provided URL, converting it into a format (documents/tool) that can be further analyzed.

4. Intelligent FAQ Generation

Tool Calling Agent: Powered by an AI agent, the workflow:
- Receives the raw website content and chat history.
- Uses a system message instructing the agent to generate FAQ questions and answers based on the webpage content.
- Converts these Q&As into Schema.org JSON-LD format, ready to be embedded in the page source for SEO.

5. Results Display

Chat Output: The generated FAQs and their Schema.org code are sent back to the user, completing the workflow.

Workflow Structure Table

Step	Component	Purpose
1. Chat Start	ChatOpenedTrigger	Detects chat session initiation
2. Welcome Message	MessageWidget	Greets user, explains purpose
3. Show Welcome	ChatOutput	Displays welcome message
4. Collect URL	ChatInput	Receives user’s URL input
5. Maintain Context	ChatHistory	Stores conversation for context
6. Fetch Website Content	URLContent (Retriever)	Retrieves content from provided URL
7. Generate FAQ & Schema	ToolCallingAgent	Creates Q&A pairs and Schema.org JSON-LD code
8. Output Results	ChatOutput	Presents final FAQs and code to user

Why Is This Workflow Useful?

Scalability: You can quickly generate structured FAQ sections for multiple web pages without manual copywriting or coding.
SEO Automation: By producing Schema.org-compliant code, your FAQ content is ready for rich results on search engines (like Google), improving visibility and click-through rates.
Consistency: Ensures that FAQs are generated in a uniform and high-quality format, reducing human error.
Time Savings: Automates both content extraction and structured data formatting, dramatically reducing the time needed to create SEO-friendly FAQs.

Potential Use Cases

Webmasters aiming to enhance search visibility for multiple pages.
Content Managers looking to scale FAQ creation for large websites or ecommerce platforms.
SEO Agencies automating structured data implementation for clients.
Product Owners wanting to improve customer support and SERP appearance.

Summary

By combining chat-based input, automated web content extraction, intelligent FAQ generation, and Schema.org formatting, this workflow streamlines and scales the process of creating SEO-optimized FAQ sections for any webpage. It is a valuable automation for anyone looking to enhance their website’s search presence and user value with minimal manual effort.

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