Proven architectural patterns for building n8n workflows.
Purpose
Teaches architectural patterns for building n8n workflows. Provides structure, best practices, and proven approaches for common use cases.
Activates On
- build workflow
- workflow pattern
- workflow architecture
- workflow structure
- webhook processing
- http api
- api integration
- database sync
- ai agent
- chatbot
- scheduled task
- automation pattern
File Count
7 files, ~3,700 lines total
Priority
HIGH - Addresses 813 webhook searches (most common use case)
Dependencies
n8n-mcp tools:
- search_nodes (find nodes for patterns)
- get_node (understand node operations)
- search_templates (find example workflows)
- ai_agents_guide (AI pattern guidance)
Related skills:
- n8n MCP Tools Expert (find and configure nodes)
- n8n Expression Syntax (write expressions in patterns)
- n8n Node Configuration (configure pattern nodes)
- n8n Validation Expert (validate pattern implementations)
Coverage
The 5 Core Patterns
-
Webhook Processing (Most Common - 813 searches)
- Receive HTTP requests → Process → Respond
- Critical gotcha: Data under $json.body
- Authentication, validation, error handling
-
HTTP API Integration (892 templates)
- Fetch from REST APIs → Transform → Store/Use
- Authentication methods, pagination, rate limiting
- Error handling and retries
-
Database Operations (456 templates)
- Read/Write/Sync database data
- Batch processing, transactions, performance
- Security: parameterized queries, read-only access
-
AI Agent Workflow (234 templates, 270 AI nodes)
- AI agents with tool access and memory
- 8 AI connection types
- ANY node can be an AI tool
-
Scheduled Tasks (28% of all workflows)
- Recurring automation workflows
- Cron schedules, timezone handling
- Monitoring and error handling
Cross-Cutting Concerns
- Data flow patterns (linear, branching, parallel, loops)
- Error handling strategies
- Performance optimization
- Security best practices
- Testing approaches
- Monitoring and logging
Evaluations
5 scenarios (100% coverage expected):
- eval-001: Webhook workflow structure
- eval-002: HTTP API integration pattern
- eval-003: Database sync pattern
- eval-004: AI agent workflow with tools
- eval-005: Scheduled report generation
Key Features
✅ 5 Proven Patterns: Webhook, HTTP API, Database, AI Agent, Scheduled tasks
✅ Complete Examples: Working workflow configurations for each pattern
✅ Best Practices: Proven approaches from real-world n8n usage
✅ Common Gotchas: Documented mistakes and their fixes
✅ Integration Guide: How patterns work with other skills
✅ Template Examples: Real examples from 2,653+ n8n templates
Files
- SKILL.md (486 lines) - Pattern overview, selection guide, checklist
- webhook_processing.md (554 lines) - Webhook patterns, data structure, auth
- http_api_integration.md (763 lines) - REST APIs, pagination, rate limiting
- database_operations.md (854 lines) - DB operations, batch processing, security
- ai_agent_workflow.md (918 lines) - AI agents, tools, memory, 8 connection types
- scheduled_tasks.md (845 lines) - Cron schedules, timezone, monitoring
- README.md (this file) - Skill metadata
Success Metrics
Expected outcomes:
- Users select appropriate pattern for their use case
- Workflows follow proven structural patterns
- Common gotchas avoided (webhook $json.body, SQL injection, etc.)
- Proper error handling implemented
- Security best practices followed
Pattern Selection Stats
Common workflow composition:
Trigger Distribution:
- Webhook: 35% (most common)
- Schedule: 28%
- Manual: 22%
- Service triggers: 15%
Transformation Nodes:
- Set: 68%
- Code: 42%
- IF: 38%
- Switch: 18%
Output Channels:
- HTTP Request: 45%
- Slack: 32%
- Database: 28%
- Email: 24%
Complexity:
- Simple (3-5 nodes): 42%
- Medium (6-10 nodes): 38%
- Complex (11+ nodes): 20%
Critical Insights
Webhook Processing:
- 813 searches (most common use case!)
- #1 gotcha: Data under $json.body (not $json directly)
- Must choose response mode: onReceived vs lastNode
API Integration:
- Authentication via credentials (never hardcode!)
- Pagination essential for large datasets
- Rate limiting prevents API bans
- continueOnFail: true for error handling
Database Operations:
- Always use parameterized queries (SQL injection prevention)
- Batch processing for large datasets
- Read-only access for AI tools
- Transaction handling for multi-step operations
AI Agents:
- 8 AI connection types (ai_languageModel, ai_tool, ai_memory, etc.)
- ANY node can be an AI tool (connect to ai_tool port)
- Memory essential for conversations (Window Buffer recommended)
- Tool descriptions critical (AI uses them to decide when to call)
Scheduled Tasks:
- Set workflow timezone explicitly (DST handling)
- Prevent overlapping executions (use locks)
- Error Trigger workflow for alerts
- Batch processing for large data
Workflow Creation Checklist
Every pattern follows this checklist:
Planning Phase
- [ ] Identify the pattern (webhook, API, database, AI, scheduled)
- [ ] List required nodes (use search_nodes)
- [ ] Understand data flow (input → transform → output)
- [ ] Plan error handling strategy
Implementation Phase
- [ ] Create workflow with appropriate trigger
- [ ] Add data source nodes
- [ ] Configure authentication/credentials
- [ ] Add transformation nodes (Set, Code, IF)
- [ ] Add output/action nodes
- [ ] Configure error handling
Validation Phase
- [ ] Validate each node configuration
- [ ] Validate complete workflow
- [ ] Test with sample data
- [ ] Handle edge cases
Deployment Phase
- [ ] Review workflow settings
- [ ] Activate workflow
- [ ] Monitor first executions
- [ ] Document workflow
Real Template Examples
Weather to Slack (Template #2947):
Schedule (daily 8 AM) → HTTP Request (weather) → Set → Slack
Webhook Processing: 1,085 templates
HTTP API Integration: 892 templates
Database Operations: 456 templates
AI Workflows: 234 templates
Use search_templates to find examples for your use case!
Integration with Other Skills
Pattern Selection (this skill):
- Identify use case
- Select appropriate pattern
- Follow pattern structure
Node Discovery (n8n MCP Tools Expert):
4. Find nodes for pattern (search_nodes)
5. Understand node operations (get_node)
Implementation (n8n Expression Syntax + Node Configuration):
6. Write expressions ({{$json.body.field}})
7. Configure nodes properly
Validation (n8n Validation Expert):
8. Validate workflow structure
9. Fix validation errors
Last Updated
2025-10-20
Part of: n8n-skills repository
Conceived by: Romuald Członkowski - www.aiadvisors.pl/en