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🧠 AI Prompt Generator Workflow – n8n Documentation

Who is this for?

This workflow is for AI builders, prompt engineers, developers, marketers, and no-code creators who want to convert rough user input into structured, high-quality prompts for LLMs. It’s especially useful for tools that rely on precision prompting and want to automate the discovery of intent and constraints.


What problem is this workflow solving? / Use case

Many users struggle to write effective prompts due to vague ideas or unclear formatting needs. This workflow:

  • Collects structured user input.
  • Dynamically generates clarifying questions.
  • Returns a well-formatted AI prompt based on the user's intent and context.

This ensures the generated prompt is useful for downstream AI agents without requiring technical understanding from the end user.


What this workflow does

  1. Start with a branded form UI
    The user is shown a styled form with questions like:

    • What do you want to build?
    • What tools can you access?
    • What input can be expected?
    • What output do you expect?
  2. Analyze and generate relevant follow-up questions
    The workflow sends the user's answers to Google Gemini (via LangChain) which outputs 1–3 clarifying questions. These questions are parsed into a dynamic form.

  3. Loop through and collect follow-up answers
    Each follow-up question is shown in a form one at a time to capture additional context.

  4. Merge all inputs
    The base intent and follow-up responses are merged into a single context block.

  5. Generate a final AI-ready prompt
    The prompt generator node formats everything into a clean, six-section structure:

    • <constraints>
    • <role>
    • <inputs>
    • <tools>
    • <instructions>
    • <conclusions>
  6. Display the final result
    The finished prompt is shown in a clean UI where users can easily copy and reuse it.


Setup

  1. Credentials Required

    • Google Gemini (PaLM) API credentials (already integrated as Google Gemini(PaLM) Api account 2).
  2. Form Trigger

    • Ensure the On form submission trigger is exposed via a webhook or public endpoint (e.g. using ngrok or deployed server).
  3. Styling

    • Custom CSS is included in all form nodes for a beautiful UI. You can modify this to match your branding.
  4. Environment

    • This workflow is compatible with self-hosted n8n or n8n.cloud.
    • Webhooks must be accessible to users who will fill out the form.

How to customize this workflow to your needs

  • Change the base questions
    Update the BaseQuestions form node to add or remove fields depending on your use case.

  • Modify Gemini prompts
    You can edit the system prompt inside PromptGenerator to change tone, output structure, or AI instructions.

  • Change prompt formatting
    If you use a different AI agent (like GPT, Claude, or Mistral), adjust the section labels and formatting to suit that agent’s expected input.

  • Send results elsewhere
    Add integration nodes after PromptGenerator, such as:

    • Google Docs / Notion (to log prompts)
    • Gmail / Slack (to notify your team)
    • Zapier / Make (to push to other automation flows)
  • Skip follow-up questions (optional)
    If your base form collects all needed info, you can bypass the RelevantQuestions form section by modifying conditional logic.


Example Output Prompt (Structure)

<role> You are an AI assistant that converts videos into LinkedIn posts with a witty tone. </role> <inputs> - A short video (max 5 minutes) - Desired tone: witty - Style: both summary and quotes - Audience: general network </inputs> <tools> You do not have access to APIs or web search. </tools> <instructions> 1. Parse transcript. 2. Extract insights and quotes. 3. Write an engaging, witty LinkedIn post under 3000 characters. </instructions> <constraints> Avoid technical jargon. No generic intros. Make it platform-native. </constraints> <conclusions> Return a LinkedIn-ready post that starts with a hook and ends with hashtags.