Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Proven architectural patterns for building n8n workflows.
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See how to installReview the instructions the agent will receive before you install.
Proven architectural patterns for building n8n workflows.
Based on analysis of real workflow usage:
Webhook Processing (Most Common)
[HTTP API Integration]
Database Operations
AI Agent Workflow
Scheduled Tasks
Webhook Processing - Use when:
HTTP API Integration - Use when:
Database Operations - Use when:
AI Agent Workflow - Use when:
Scheduled Tasks - Use when:
All patterns share these building blocks:
When building ANY workflow, follow this checklist:
activateWorkflow operationTrigger → Transform → Action → End
Use when: Simple workflows with single path
Trigger → IF → [True Path]
└→ [False Path]
Use when: Different actions based on conditions
Trigger → [Branch 1] → Merge
└→ [Branch 2] ↗
Use when: Independent operations that can run simultaneously
Trigger → Split in Batches → Process → Loop (until done)
Use when: Processing large datasets in chunks
Main Flow → [Success Path]
└→ [Error Trigger → Error Handler]
Use when: Need separate error handling workflow
Problem: Can't access webhook payload data
Solution: Data is nested under $json.body
❌ {{$json.email}}
✅ {{$json.body.email}}
See: n8n Expression Syntax skill
Problem: Node processes all input items, but I only want one
Solution: Use "Execute Once" mode or process first item only
{{$json[0].field}} // First item only
Problem: API calls failing with 401/403
Solution:
Problem: Nodes executing in unexpected order
Solution: Check workflow settings → Execution Order
Problem: Expressions showing as literal text
Solution: Use {{}} around expressions
These skills work together with Workflow Patterns:
n8n MCP Tools Expert - Use to:
n8n Expression Syntax - Use to:
n8n Node Configuration - Use to:
n8n Validation Expert - Use to:
Common workflow patterns:
Most Common Triggers:
Most Common Transformations:
Most Common Outputs:
Average Workflow Complexity:
1. Webhook (path: "form-submit", POST)
2. Set (map form fields)
3. Slack (post message to #notifications)
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)
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)
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)
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)
For comprehensive guidance on each pattern:
From n8n template library:
Template #2947: Weather to Slack
Webhook Processing: Most common pattern
HTTP API: Common pattern
Database Operations: Common pattern
AI Agents: Growing in usage
Use search_templates and get_template from n8n-mcp tools to find examples!
Key Points:
Next Steps:
Related Skills:
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Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.
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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
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agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
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