Multi-Agent Deep Research and Lead Magnet Generator - n8n Workflow

Marketing Teams needing high-quality, research-backed content quickly.
Sales Enablement Specialists creating educational lead magnets for prospecting.
Technical Content Writers who want to leverage n8n and AI agents for structured drafting.
Developers looking for advanced n8n templates for LangChain orchestration.

Generating deeply researched, actionable content for sales lead magnets typically requires significant time from researchers, planners, writers, and editors. This advanced n8n workflow solves this by orchestrating a sequence of specialized AI agents (Query Builder, Research Leader, Project Planner, and Team of Research Assistants) to execute the entire content lifecycle automatically.

This robust n8n automation is specifically designed to create content centered around the 'Trigify' product, leveraging proprietary knowledge bases while supplementing with general web research (via the Perplexity tool). The resulting document is highly structured, action-oriented, and immediately published to Google Docs, offering a complete, end-to-end content production solution built entirely in n8n.

This powerful n8n workflow begins with the When chat message received n8n trigger, which accepts the topic for the lead magnet.

1. Query Refinement: The input topic is sent to the Query Builder agent, which refines it into five highly targeted search queries. This agent uses conditional logic to access the Trigify knowledge hub2 tool if the topic is product-specific.


2. Strategic Planning: The refined queries proceed to the Research Leader agent. This n8n node synthesizes the research (using the Perplexity and Trigify tools) and structures the findings into a comprehensive Table of Contents (TOC).


3. Prompt Generation: The TOC is passed to the Project Planner agent. This agent generates the overall article structure (title, subtitle, introduction, conclusion) and creates highly detailed, exhaustive prompts for every chapter outlined in the TOC.


4. Parallel Drafting: The Split Out n8n node separates the chapter prompts, allowing the Team of Research Assistants agent (running multiple instances in parallel) to draft the individual chapter content in HTML format. Each chapter draft is instruction-heavy, focused on actionable, step-by-step guidance.


5. Assembly and Polish: The Merge n8n node combines the drafted chapters. A Code n8n node then organizes this content alongside the introduction and conclusion for the final editing stage. The Editor agent performs a final, comprehensive editorial pass, ensuring tone consistency and flow.


6. Publishing: The final article is created in Google Docs, inserted using the Google Docs1 n8n node, and then instantly shared publicly using the Google Drive n8n node. The final output is the shareable URL of the newly generated document.

To deploy this complex n8n workflow and start generating lead magnets, follow these steps:

1. Import the n8n template: Copy the provided JSON code and paste it into your n8n instance using the 'New' -> 'Import from JSON' option.


2. Set up Credentials: This n8n workflow requires multiple credentials:

1. Activate the Trigger: Ensure the When chat message received n8n trigger is configured to receive input from your desired source (e.g., internal chat application or custom frontend integration).


2. Test the n8n workflow: Run a manual test execution to verify that all chained agents (the Query Builder, Research Leader, and Project Planner n8n nodes) correctly execute and produce structured JSON output, leading to a successful document creation.

When chat message received (n8n trigger): The starting point of the n8n workflow, accepting the topic for the lead magnet from an input source.
Query Builder (LangChain Agent n8n node): Refines the user-provided topic into five specific search queries. Key configuration involves a detailed system message that enforces strict JSON output (via the Structured Output Parser n8n node) and instructs the agent to use both general (Perplexity tool) and specialized (Trigify knowledge hub2) research tools.
Research Leader (LangChain Agent n8n node): Takes the five queries and conducts deep research to create a comprehensive Table of Contents (TOC). The system message mandates an actionable, step-by-step approach, especially for 'Trigify' related content.
Project Planner (LangChain Agent n8n node): Structures the final article, generating the title, subtitle, introduction, conclusion, and exhaustive content prompts for each chapter based on the TOC. It uses the Structured Output Parser1 n8n node to ensure structured JSON output.
Split Out (n8n node): Splits the array of chapter prompts from the Project Planner into individual items, enabling parallel processing by the writing agents.
Team of Research Assistants (LangChain Agent n8n node): Writes the full chapter text for each item in the workflow. It uses HTML formatting for output and references previous/next chapters to ensure flow. Crucially, it uses the Trigify knowledge hub tool for accurate product-specific citations.
Editor (LangChain Agent n8n node): The final AI stage. It aggregates the raw content and polishes it into a cohesive article, adjusting the tone to be formal but casual, and inserting image placeholders.
Google Docs (n8n node): Creates the new document in the specified folder, naming it dynamically using the title generated by the Project Planner agent.

• Google Drive (n8n node): Sets the sharing permission for the generated document to 'anyone with the link can view' (reader role).