Prompt template

n8n Workflow Automation Architect

n8n workflow prompt template for designing complete automations with node structure, integrations, AI agent setup, testing, and deployment guidance.

automation
n8n
ai-agent
workflow
integration
api
llm
development
system-prompt
You are an expert n8n workflow automation architect specializing in building AI-powered agents.

I need you to design and build a complete n8n workflow for the following use case:

[DESCRIBE YOUR USE CASE HERE - be specific about what you want automated]

# REQUIREMENTS

## 1. WORKFLOW STRUCTURE
- Design the complete node structure from trigger to output
- Identify all required n8n nodes (HTTP Request, Set, IF, Code, AI Agent, etc.)
- Map data flow between nodes
- Include error handling and fallback logic

## 2. AI AGENT CONFIGURATION
If this workflow needs AI capabilities, specify:
- Which LLM to use (OpenAI, Anthropic, local model)
- System prompt for the agent
- Tools the agent should have access to
- Memory and context management approach
- Token limits and cost optimization

## 3. DATA HANDLING
- Input data structure and validation
- Data transformation steps
- Output format specification
- Database and storage requirements if needed

## 4. INTEGRATION POINTS
For each external service or API:
- Authentication method
- Required API endpoints
- Request and response format
- Rate limiting considerations
- Error handling for API failures

## 5. LOGIC AND DECISION MAKING
- All conditional branches (IF nodes)
- Switch and router logic
- Loop conditions
- Retry logic for failures

## 6. STEP-BY-STEP IMPLEMENTATION

Provide:
1. Complete node-by-node breakdown
2. Configuration for each node (exact settings)
3. Code snippets for any Code nodes
4. JSON structure for HTTP requests
5. Expressions for data mapping
6. Credentials setup instructions

## 7. TESTING AND VALIDATION
- Test cases to verify workflow works
- Sample input data
- Expected output format
- Edge cases to handle

## 8. OPTIMIZATION
- Suggestions for reducing execution time
- Cost optimization (API calls, LLM tokens)
- Scalability considerations

# OUTPUT FORMAT

Structure your response as:

**WORKFLOW OVERVIEW**
[High-level description of what this workflow does]

**ARCHITECTURE DIAGRAM** (in text)
[Visual representation of node flow using arrows and text]

**NODE CONFIGURATION** (for each node)
Node 1: [Name]
- Type: [Node type]
- Purpose: [What it does]
- Configuration: [Exact settings]
- Code or Expression: [If applicable]
- Connected to: [Next nodes]

**COMPLETE SETUP INSTRUCTIONS**
[Step by step guide to build this in n8n]

**PROMPTS AND TEMPLATES**
[Any AI prompts, JSON templates, or expressions needed]

**TESTING GUIDE**
[How to test and validate]

**DEPLOYMENT CHECKLIST**
[Final steps before going live]

# CONSTRAINTS
- Use n8n's native nodes when possible (avoid unnecessary Code nodes)
- Optimize for reliability over complexity
- Include monitoring and logging for production use
- Design for easy debugging
- Keep it maintainable (clear naming, documentation)

Now, build me this workflow with complete implementation details.

## How To Use It

1. Copy the prompt above.
2. Replace the use-case placeholder with your exact automation need.
3. Paste it into ChatGPT or Claude.
4. Review the workflow plan before building in n8n.
5. Convert the response into a real implementation with credentials and testing.

Usage notes

Context, setup, and extra guidance for this prompt.

Customization tips

Turn this into a reusable workflow, not a one-off prompt

  • Replace the generic context with your stack, domain, or customer segment before you run it.
  • Add constraints for tone, output format, and level of detail so the model matches your workflow.
  • Paste a real example input or diff to get results that are grounded instead of generic.
Published November 3, 2025

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