n8n-workflow-patterns
Skill4 starsChanged 5 months agoMITView on GitHub
Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, or scheduled tasks.
23 other projects use a version of this, 19 of them edited.
Adopted by
Most recently taken up by
- delorenj/skillsedited, first seen Nov 7, 2026
- Mfrostbutter/n8n-workflow-harnessedited, first seen Nov 1, 2026
- WilkoMarketing/antigravity-n8n-skillsedited, first seen Oct 6, 2026
- nomdedev/agent-manager-templateedited, first seen Sep 30, 2026
- jawwad-ali/claude-code-skillsedited, first seen Sep 5, 2026
- czlonkowski/n8n-skillsedited, first seen Aug 29, 2026
Used with
Projects with it also use n8n-code-tool, n8n-multi-instance and 9 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
czlonkowskiSkilln8n-code-tool
Write JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will invoke, parsing the `query` input, returning a string result, defining an input schema for structured arguments (specifyInputSchema, jsonSchemaExample, DynamicStructuredTool), or troubleshooting errors like \"Wrong output type returned\", \"No execution data available\", \"The response property should be a string, but it is an object\", \"Cannot assign to read only property 'name'\", or an AI agent that refuses to call the tool. Covers the critical differences between Code node and Code Tool: return format (string vs `[{json:{...}}]`), unavailability of `$fromAI`/`$input`/`$helpers` in the Code Tool sandbox, naming rules for AI invocation, and when to use `toolWorkflow`/HTTP Request Tool instead.
Also in 3 projects that use this
czlonkowskiSkilln8n-multi-instance
Use when an n8n-mcp account targets more than one n8n instance — i.e. the `n8n_instances` tool is available, the user mentions multiple n8n instances or environments (prod vs staging, several teams or clients), several agents or chats work on one account in parallel, a workflow / datatable / credential / execution call returns an unexpected NOT_FOUND or reads data you don't recognize, or a call is refused with `INSTANCE_AMBIGUOUS` or `INSTANCE_NOT_FOUND`. Covers naming the target instance on each call with the `instance` argument, setting the default with `switch`, verifying the target before high-stakes work — credential writes above all — and recovering from misroutes and fail-closes. Always consult this skill before operating on a specific instance, before any credential create/update/delete on a multi-instance account, or when a call hits the wrong/empty data or an instance error.
Also in 3 projects that use this
tmolaviSkilln8n-agents
Use when building n8n AI Agent / LangChain clusters — tools, memory, RAG, structured output, system prompts, sub-workflow-as-tool, or fixing agent connection topology (ai_languageModel, ai_tool, ai_memory).
Also in 3 projects that use this
tmolaviSkilln8n-error-handling
Use for production n8n workflows, webhook APIs, retries, error outputs, error workflows, dead-letter patterns, and correct HTTP response status shapes for callers.
Also in 3 projects that use this
silvainfmSkillmarketing-ideas
When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing ideas,' 'growth ideas,' 'how to market,' 'marketing strategies,' 'marketing tactics,' 'ways to promote,' or 'ideas to grow.' This skill provides 140 proven marketing approaches organized by category.
Also in 3 projects that use this
silvainfmSkillpricing-strategy
When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' or 'monetization.' This skill covers pricing research, tier structure, and packaging strategy.
Also in 3 projects that use this
- +3 more from czlonkowski
- +1 more from tmolavi
Other versions23 projects use a version of this.
Word for word · 2
- promptadvisers/n8n-powerhouse★ 9100% same
- refineryconnect/n8n-powerhouse★ 0100% same
Edited · 19
- czlonkowski/n8n-skills★ 6.5k38% same
- WilkoMarketing/antigravity-n8n-skills★ 10638% same
- Fandry96/k3-agentic-skills★ 2792% same
- leadgenjay/claude-skills★ 2291% same
- delorenj/skills★ 1749% same
- eugenepyvovarov/mcpbundler-agent-skills-marketplace★ 1298% same
- CarbeneAI/Forge★ 998% same
- reachmeshailesh-boop/codex-skill-pack★ 998% same
- jawwad-ali/claude-code-skills★ 498% same
- computer-agents/skills★ 298% same
9 more not listed
Wrote their own version · 2
- walidboulanouar/n8n-claude-code-template★ 19same name
- tygwan/skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
Show its rules and text
We split this skill into the rules it gives an agent
35 rules. 33 are common, 0 are distinctive, and 2 are very specific to this project.
33
Common
Most of the 21 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 25
Read/Write/Sync database data
- Common: line 42
Webhook Processing: - Use when:
- Common: line 48
HTTP API Integration: - Use when:
- Common: line 54
Database Operations: - Use when:
- Common: line 60
AI Agent Workflow: - Use when:
- Common: line 66
Scheduled Tasks: - Use when:
- Common: line 76
All patterns share these building blocks:
- Common: line 82
Polling: - Check for changes (intervals)
- Common: line 97
HTTP Request: - Call APIs
- Common: line 104
IF - Check for error conditions
- Common: line 112
When building ANY workflow, follow this checklist:
- Common: line 194
Solution: Use "Execute Once" mode or process first item only
- Common: line 204
Use the "Credentials" section, not parameters
- Common: line 205
Test credentials before workflow activation
- Common: line 210
Solution: Check workflow settings → Execution Order
- Common: line 217
Solution: Use {{}} around expressions
- Common: line 226
n8n MCP Tools Expert: - Use to:
- Common: line 229
Create workflows (n8n_create_workflow)
- Common: line 231
n8n Expression Syntax: - Use to:
- Common: line 232
Write expressions in transformation nodes
- Common: line 236
n8n Node Configuration: - Use to:
- Common: line 240
n8n Validation Expert: - Use to:
- Common: line 243
Ensure workflow correctness before deployment
- Very specific: line 359
Use search_templates and get_template from n8n-mcp tools to find examples!
- Common: line 367
Start with the simplest pattern that solves your problem
- Common: line 369
Use error handling on all workflows
- Common: line 370
Test with sample data before activation
- Common: line 371
Follow the workflow creation checklist
- Common: line 372
Use descriptive node names
- Common: line 373
Document complex workflows (notes field)
- Common: line 381
Use complex patterns when simple ones suffice
- Common: line 394
Use the workflow creation checklist for every workflow
- Common: line 400
Read the detailed pattern file
- Common: line 401
Use n8n MCP Tools Expert to find nodes
- Common: line 403
Use n8n Validation Expert to validate
“Common” is measured: kept by at least 6 in 10 of the 21 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
n8n Workflow Patterns
Proven architectural patterns for building n8n workflows.
The 5 Core Patterns
Based on analysis of real workflow usage:
- Webhook Processing (Most Common)
- Receive HTTP requests → Process → Output
- Pattern: Webhook → Validate → Transform → Respond/Notify
- HTTP API Integration
- Fetch from REST APIs → Transform → Store/Use
- Pattern: Trigger → HTTP Request → Transform → Action → Error Handler
- Database Operations
- Read/Write/Sync database data
- Pattern: Schedule → Query → Transform → Write → Verify
- AI Agent Workflow
- AI agents with tools and memory
- Pattern: Trigger → AI Agent (Model + Tools + Memory) → Output
- Scheduled Tasks
- Recurring automation workflows
- Pattern: Schedule → Fetch → Process → Deliver → Log
Pattern Selection Guide
When to use each pattern:
Webhook Processing - Use when:
- Receiving data from external systems
- Building integrations (Slack commands, form submissions, GitHub webhooks)
- Need instant response to events
- Example: "Receive Stripe payment webhook → Update database → Send confirmation"
HTTP API Integration - Use when:
- Fetching data from external APIs
- Synchronizing with third-party services
- Building data pipelines
- Example: "Fetch GitHub issues → Transform → Create Jira tickets"
Database Operations - Use when:
- Syncing between databases
- Running database queries on schedule
- ETL workflows
- Example: "Read Postgres records → Transform → Write to MySQL"
AI Agent Workflow - Use when:
- Building conversational AI
- Need AI with tool access
- Multi-step reasoning tasks
- Example: "Chat with AI that can search docs, query database, send emails"
Scheduled Tasks - Use when:
- Recurring reports or summaries
- Periodic data fetching
- Maintenance tasks
- Example: "Daily: Fetch analytics → Generate report → Email team"
Common Workflow Components
All patterns share these building blocks:
1. Triggers
- Webhook - HTTP endpoint (instant)
- Schedule - Cron-based timing (periodic)
- Manual - Click to execute (testing)
- Polling - Check for changes (intervals)
2. Data Sources
- HTTP Request - REST APIs
- Database nodes - Postgres, MySQL, MongoDB
- Service nodes - Slack, Google Sheets, etc.
- Code - Custom JavaScript/Python
3. Transformation
- Set - Map/transform fields
- Code - Complex logic
- IF/Switch - Conditional routing
- Merge - Combine data streams
4. Outputs
- HTTP Request - Call APIs
- Database - Write data
- Communication - Email, Slack, Discord
- Storage - Files, cloud storage
5. Error Handling
- Error Trigger - Catch workflow errors
- IF - Check for error conditions
- Stop and Error - Explicit failure
- Continue On Fail - Per-node setting
Workflow Creation Checklist
When building ANY workflow, follow 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_node_operation)
- Validate complete workflow (validate_workflow)
- Test with sample data
- Handle edge cases (empty data, errors)
Deployment Phase
- Review workflow settings (execution order, timeout, error handling)
- Activate workflow ⚠️ Manual activation required in n8n UI (API/MCP cannot activate)
- Monitor first executions
- Document workflow purpose and data flow
Data Flow Patterns
Linear Flow
Trigger → Transform → Action → EndUse when: Simple workflows with single path
Branching Flow
Trigger → IF → [True Path]
└→ [False Path]Use when: Different actions based on conditions
Parallel Processing
Trigger → [Branch 1] → Merge
└→ [Branch 2] ↗Use when: Independent operations that can run simultaneously
Loop Pattern
Trigger → Split in Batches → Process → Loop (until done)Use when: Processing large datasets in chunks
Error Handler Pattern
Main Flow → [Success Path]
└→ [Error Trigger → Error Handler]Use when: Need separate error handling workflow
Common Gotchas
1. Webhook Data Structure
Problem: Can't access webhook payload data
Solution: Data is nested under $json.body
❌ {{$json.email}}
✅ {{$json.body.email}}See: n8n Expression Syntax skill
2. Multiple Input Items
Problem: Node processes all input items, but I only want one
Solution: Use "Execute Once" mode or process first item only
{{$json[0].field}} // First item only3. Authentication Issues
Problem: API calls failing with 401/403
Solution:
- Configure credentials properly
- Use the "Credentials" section, not parameters
- Test credentials before workflow activation
4. Node Execution Order
Problem: Nodes executing in unexpected order
Solution: Check workflow settings → Execution Order
- v0: Top-to-bottom (legacy)
- v1: Connection-based (recommended)
5. Expression Errors
Problem: Expressions showing as literal text
Solution: Use {{}} around expressions
- See n8n Expression Syntax skill for details
Integration with Other Skills
These skills work together with Workflow Patterns:
n8n MCP Tools Expert - Use to:
- Find nodes for your pattern (search_nodes)
- Understand node operations (get_node_essentials)
- Create workflows (n8n_create_workflow)
n8n Expression Syntax - Use to:
- Write expressions in transformation nodes
- Access webhook data correctly ({{$json.body.field}})
- Reference previous nodes ({{$node["Node Name"].json.field}})
n8n Node Configuration - Use to:
- Configure specific operations for pattern nodes
- Understand node-specific requirements
n8n Validation Expert - Use to:
- Validate workflow structure
- Fix validation errors
- Ensure workflow correctness before deployment
Pattern Statistics
Common workflow patterns:
Most Common Triggers:
- Webhook - 35%
- Schedule (periodic tasks) - 28%
- Manual (testing/admin) - 22%
- Service triggers (Slack, email, etc.) - 15%
Most Common Transformations:
- Set (field mapping) - 68%
- Code (custom logic) - 42%
- IF (conditional routing) - 38%
- Switch (multi-condition) - 18%
Most Common Outputs:
- HTTP Request (APIs) - 45%
- Slack - 32%
- Database writes - 28%
- Email - 24%
Average Workflow Complexity:
- Simple (3-5 nodes): 42%
- Medium (6-10 nodes): 38%
- Complex (11+ nodes): 20%
Quick Start Examples
Example 1: Simple Webhook → Slack
1. Webhook (path: "form-submit", POST)
2. Set (map form fields)
3. Slack (post message to #notifications)Example 2: Scheduled Report
1. Schedule (daily at 9 AM)
2. HTTP Request (fetch analytics)
3. Code (aggregate data)
4. Email (send formatted report)
5. Error Trigger → Slack (notify on failure)Example 3: Database Sync
1. Schedule (every 15 minutes)
2. Postgres (query new records)
3. IF (check if records exist)
4. MySQL (insert records)
5. Postgres (update sync timestamp)Example 4: AI Assistant
1. Webhook (receive chat message)
2. AI Agent
├─ OpenAI Chat Model (ai_languageModel)
├─ HTTP Request Tool (ai_tool)
├─ Database Tool (ai_tool)
└─ Window Buffer Memory (ai_memory)
3. Webhook Response (send AI reply)Example 5: API Integration
1. Manual Trigger (for testing)
2. HTTP Request (GET /api/users)
3. Split In Batches (process 100 at a time)
4. Set (transform user data)
5. Postgres (upsert users)
6. Loop (back to step 3 until done)Detailed Pattern Files
For comprehensive guidance on each pattern:
- webhook_processing.md - Webhook patterns, data structure, response handling
- http_api_integration.md - REST APIs, authentication, pagination, retries
- database_operations.md - Queries, sync, transactions, batch processing
- ai_agent_workflow.md - AI agents, tools, memory, langchain nodes
- scheduled_tasks.md - Cron schedules, reports, maintenance tasks
Real Template Examples
From n8n template library:
Template #2947: Weather to Slack
- Pattern: Scheduled Task
- Nodes: Schedule → HTTP Request (weather API) → Set → Slack
- Complexity: Simple (4 nodes)
Webhook Processing: Most common pattern
- Most common: Form submissions, payment webhooks, chat integrations
HTTP API: Common pattern
- Most common: Data fetching, third-party integrations
Database Operations: Common pattern
- Most common: ETL, data sync, backup workflows
AI Agents: Growing in usage
- Most common: Chatbots, content generation, data analysis
Use search_templates and get_template from n8n-mcp tools to find examples!
Best Practices
✅ Do
- Start with the simplest pattern that solves your problem
- Plan your workflow structure before building
- Use error handling on all workflows
- Test with sample data before activation
- Follow the workflow creation checklist
- Use descriptive node names
- Document complex workflows (notes field)
- Monitor workflow executions after deployment
❌ Don't
- Build workflows in one shot (iterate! avg 56s between edits)
- Skip validation before activation
- Ignore error scenarios
- Use complex patterns when simple ones suffice
- Hardcode credentials in parameters
- Forget to handle empty data cases
- Mix multiple patterns without clear boundaries
- Deploy without testing
Summary
Key Points:
- 5 core patterns cover 90%+ of workflow use cases
- Webhook processing is the most common pattern
- Use the workflow creation checklist for every workflow
- Plan pattern → Select nodes → Build → Validate → Deploy
- Integrate with other skills for complete workflow development
Next Steps:
- Identify your use case pattern
- Read the detailed pattern file
- Use n8n MCP Tools Expert to find nodes
- Follow the workflow creation checklist
- Use n8n Validation Expert to validate
Related Skills:
- n8n MCP Tools Expert - Find and configure nodes
- n8n Expression Syntax - Write expressions correctly
- n8n Validation Expert - Validate and fix errors
- n8n Node Configuration - Configure specific operations
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