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echoleesongecholeesong/claude-skills-plugin/skills/n8n-workflow-patterns/SKILL.md

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.

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Projects with it also use n8n-code-tool, n8n-multi-instance and 9 more.

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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.
  • czlonkowskiSkill

    n8n-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

  • czlonkowskiSkill

    n8n-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

  • tmolaviSkill

    n8n-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

  • tmolaviSkill

    n8n-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

  • silvainfmSkill

    marketing-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

  • silvainfmSkill

    pricing-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

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
  1. Very specific:

    Read/Write/Sync database data

    line 25
  2. Common:

    Webhook Processing: - Use when:

    line 42
  3. Common:

    HTTP API Integration: - Use when:

    line 48
  4. Common:

    Database Operations: - Use when:

    line 54
  5. Common:

    AI Agent Workflow: - Use when:

    line 60
  6. Common:

    Scheduled Tasks: - Use when:

    line 66
  7. Common:

    All patterns share these building blocks:

    line 76
  8. Common:

    Polling: - Check for changes (intervals)

    line 82
  9. Common:

    HTTP Request: - Call APIs

    line 97
  10. Common:

    IF - Check for error conditions

    line 104
  11. Common:

    When building ANY workflow, follow this checklist:

    line 112
  12. Common:

    Solution: Use "Execute Once" mode or process first item only

    line 194
  13. Common:

    Use the "Credentials" section, not parameters

    line 204
  14. Common:

    Test credentials before workflow activation

    line 205
  15. Common:

    Solution: Check workflow settings → Execution Order

    line 210
  16. Common:

    Solution: Use {{}} around expressions

    line 217
  17. Common:

    n8n MCP Tools Expert: - Use to:

    line 226
  18. Common:

    Create workflows (n8n_create_workflow)

    line 229
  19. Common:

    n8n Expression Syntax: - Use to:

    line 231
  20. Common:

    Write expressions in transformation nodes

    line 232
  21. Common:

    n8n Node Configuration: - Use to:

    line 236
  22. Common:

    n8n Validation Expert: - Use to:

    line 240
  23. Common:

    Ensure workflow correctness before deployment

    line 243
  24. Very specific:

    Use search_templates and get_template from n8n-mcp tools to find examples!

    line 359
  25. Common:

    Start with the simplest pattern that solves your problem

    line 367
  26. Common:

    Use error handling on all workflows

    line 369
  27. Common:

    Test with sample data before activation

    line 370
  28. Common:

    Follow the workflow creation checklist

    line 371
  29. Common:

    Use descriptive node names

    line 372
  30. Common:

    Document complex workflows (notes field)

    line 373
  31. Common:

    Use complex patterns when simple ones suffice

    line 381
  32. Common:

    Use the workflow creation checklist for every workflow

    line 394
  33. Common:

    Read the detailed pattern file

    line 400
  34. Common:

    Use n8n MCP Tools Expert to find nodes

    line 401
  35. Common:

    Use n8n Validation Expert to validate

    line 403

“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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

n8n Workflow Patterns

Proven architectural patterns for building n8n workflows.


The 5 Core Patterns

Based on analysis of real workflow usage:

  1. Webhook Processing (Most Common)
    • Receive HTTP requests → Process → Output
    • Pattern: Webhook → Validate → Transform → Respond/Notify
  2. HTTP API Integration
    • Fetch from REST APIs → Transform → Store/Use
    • Pattern: Trigger → HTTP Request → Transform → Action → Error Handler
  3. Database Operations
    • Read/Write/Sync database data
    • Pattern: Schedule → Query → Transform → Write → Verify
  4. AI Agent Workflow
    • AI agents with tools and memory
    • Pattern: Trigger → AI Agent (Model + Tools + Memory) → Output
  5. 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 → End

Use 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 only

3. 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:

  1. Webhook - 35%
  2. Schedule (periodic tasks) - 28%
  3. Manual (testing/admin) - 22%
  4. Service triggers (Slack, email, etc.) - 15%

Most Common Transformations:

  1. Set (field mapping) - 68%
  2. Code (custom logic) - 42%
  3. IF (conditional routing) - 38%
  4. Switch (multi-condition) - 18%

Most Common Outputs:

  1. HTTP Request (APIs) - 45%
  2. Slack - 32%
  3. Database writes - 28%
  4. 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:

  1. 5 core patterns cover 90%+ of workflow use cases
  2. Webhook processing is the most common pattern
  3. Use the workflow creation checklist for every workflow
  4. Plan pattern → Select nodes → Build → Validate → Deploy
  5. Integrate with other skills for complete workflow development

Next Steps:

  1. Identify your use case pattern
  2. Read the detailed pattern file
  3. Use n8n MCP Tools Expert to find nodes
  4. Follow the workflow creation checklist
  5. 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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