Prompt for Section Deduplication and Refinement
Prompt instructing the LLM to analyze input content, remove repetition, and refine it within a word limit.
Generate comprehensive, SEO-optimized blog posts with advanced structure and high word count using multiple AI agents. The workflow includes automated research, outlines, drafting, SEO enrichment, rephrasing, and final export, making it ideal for content marketing teams seeking high-quality, educational, and non-repetitive blog articles.

Flows
Prompt instructing the LLM to analyze input content, remove repetition, and refine it within a word limit.
Prompt for LLM to generate a content brief for a blog post, emphasizing non-repetition, educational value, and structural requirements.
Prompt for LLM to write one section of an educational blog, with specific instructions for headlines, tone, and formatting.
Advanced AI agent acting as a professional blog copywriter for generating detailed, non-repetitive content briefs.
LLM agent acting as a manager, ensuring high quality, non-repetitive, instructional blog content.
LLM agent responsible for quality control and elimination of repeated content in a blog.
LLM agent acting as an expert copywriter, tasked with scientific, comprehensive section writing, avoiding repetition.
LLM agent acting as a professional author, focusing on rephrasing text for clarity, natural tone, and educational value.
LLM agent acting as an expert SEO specialist, extracting SEO-related information for articles.
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.
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.
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.
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.
The Structured Output Generator component lets you create precise, structured data from any input prompt using your chosen LLM model. Define the exact data fields and output format you want, ensuring consistent and reliable responses for advanced AI workflows.
The Create Data component enables you to dynamically generate structured data records with a customizable number of fields. Ideal for workflows that require the creation of new data objects on the fly, it supports flexible field configuration and seamless integration with other automation steps.
Combine multiple data sources effortlessly with the Merge Data component in FlowHunt. This versatile block collects and merges input data, streamlining workflows that require unified information handling.
The Iterator component in FlowHunt automates repetitive tasks by executing a subflow or external flow for each item in a list. Ideal for batch processing, data enrichment, or applying the same logic to multiple inputs, it supports customizable concurrency and advanced options for flexible workflow automation.
The AI Agent component in FlowHunt empowers your workflows with autonomous decision-making and tool-using capabilities. It leverages large language models and connects to various tools to solve tasks, follow goals, and provide intelligent responses. Ideal for building advanced automations and interactive AI solutions.
FlowHunt supports dozens of text generation models, including models by OpenAI. Here's how to use ChatGPT in your AI tools and chatbots.
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.
FlowHunt's GoogleSearch component enhances chatbot accuracy using Retrieval-Augmented Generation (RAG) to access up-to-date knowledge from Google. Control results with options like language, country, and query prefixes for precise and relevant outputs.
The SelfManaged Task component enables users to define and execute autonomous tasks within a workflow. Specify a clear task description, expected outcome, and assign an agent to manage execution—ideal for building structured, hierarchical automation in your flows.
Unlock advanced collaboration in FlowHunt with the Self-Managed Crew component. Coordinate multiple AI agents under a manager agent to autonomously handle complex workflows and hierarchical tasks, maximizing efficiency and scalability.
The Parse Data component transforms structured data into plain text using customizable templates. It enables flexible formatting and conversion of data inputs for further use in your workflow, helping to standardize or prepare information for downstream components.
Transform text into ready-to-download PDF files with the Export to PDF component in FlowHunt. Seamlessly convert markdown or plain text from your workflow into a PDF document, ideal for generating reports, summaries, or formatted documents on demand.
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.
The Sequential Task component organizes workflow steps by defining a clear task description, expected output, and assigning an agent to execute the task. Ideal for structured, multi-step processes, it ensures each step is well-documented and assigned, supporting complex automations in FlowHunt.
Experience organized workflow automation with the Sequential Crew component in FlowHunt. This component allows you to group multiple agent tasks and execute them one after another, making it ideal for processes that require clear, step-by-step task processing.
The Run Flow component in FlowHunt lets you trigger and execute another workflow within your current flow. Pass inputs, variables, and control how flows interact, enabling modular and reusable automation. Ideal for chaining workflows or using flows as tools.
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.
Unlock custom workflows with the Custom Trigger component in FlowHunt. This component allows users to define specific trigger points within their flow, enabling tailored actions based on custom events or inputs. Essential for building interactive and flexible automation workflows.
Effortlessly chat with any Wikipedia page using FlowHunt's AI Agents. Get concise summaries, source links, and turn hours of research into interactive insights.
FlowHunt supports dozens of AI models, including Claude models by Anthropic. Learn how to use Claude in your AI tools and chatbots with customizable settings for tailored responses.
Flow description
The Advanced Blog Generator is a complex, multi-agent workflow designed to generate high-quality, long-form blog posts on specific topics. It leverages a collaborative crew of AI agents, each with specialized roles, to automate the entire process—from research and content structuring to writing, SEO optimization, quality control, and final export. This flow is ideal for creating comprehensive, well-structured blog articles that require in-depth research, SEO best practices, and a natural, educational tone.
| Agent/Component | Role/Function |
|---|---|
| User Input | Provides topic/keyword and optional context |
| Google Search, Wikipedia | Gathers relevant research data |
| Content Brief Agent | Creates a detailed, non-repetitive content outline |
| Manager Agent | Ensures educational, scientific accuracy and structure |
| Researcher Agent | Writes section drafts based on the brief and research |
| AI Rephraser | Refines style for naturalness and AI detector evasion |
| Quality Control Agent | Removes redundancy and optimizes for readability and length |
| SEO Agent | Extracts/generates SEO metadata |
| Output/Export Modules | Assembles, formats, and exports the final blog as PDF |
This workflow is perfect for agencies, educators, publishers, and content creators who need to generate authoritative, SEO-friendly, and educational blog posts at scale. By leveraging advanced AI orchestration, it ensures both depth of research and high editorial standards—key for ranking well in search engines and delivering real value to readers.
| Step | What Happens |
|---|---|
| 1. Input Topic | User provides topic or keyword |
| 2. Research | AI gathers top articles, Wikipedia data, more |
| 3. Content Brief | AI creates an advanced, structured outline (headlines, keywords, FAQs, meta) |
| 4. Section Writing | AI writes each section, grounded in research and brief |
| 5. Humanization | AI rephrases for natural, engaging, human-like tone |
| 6. Quality Control | AI checks for redundancy, merges repeats, finalizes structure |
| 7. SEO Extraction | AI generates title, meta, URL, image ALTs, word count |
| 8. Export | Blog and SEO info parsed, formatted, and exported as PDF |
By using this flow, you can reliably automate the creation of complex, long-form blogs that meet professional standards for structure, readability, SEO, and educational value—all with minimal manual oversight.
We help companies like yours to develop smart chatbots, MCP Servers, AI tools or other types of AI automation to replace human in repetitive tasks in your organization.
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