n8n-workflow-patterns

Name: n8n-workflow-patterns
Author: czlonkowski

8.9kinstalls983forks

How to install n8n-workflow-patterns?

czlonkowski/n8n-skills/n8n-workflow-patterns

$npx -y skills add czlonkowski/n8n-skills --skill n8n-workflow-patterns

Installs into the current project.

Summary

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 workf

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SKILL.md

1	# n8n Workflow Patterns
2
3	Proven architectural patterns for building n8n workflows.
4
5	---
6
7	## The 6 Core Patterns
8
9	Based on analysis of real workflow usage:
10
11	1. [Webhook Processing](webhook_processing.md) (Most Common)
12	- Receive HTTP requests → Process → Output
13	- Pattern: Webhook → Validate → Transform → Respond/Notify
14
15	2. [HTTP API Integration](http_api_integration.md)
16	- Fetch from REST APIs → Transform → Store/Use
17	- Pattern: Trigger → HTTP Request → Transform → Action → Error Handler
18
19	3. [Database Operations](database_operations.md)
20	- Read/Write/Sync database data
21	- Pattern: Schedule → Query → Transform → Write → Verify
22
23	4. [AI Agent Workflow](ai_agent_workflow.md)
24	- AI agents with tools and memory
25	- Pattern: Trigger → AI Agent (Model + Tools + Memory) → Output
26
27	5. [Scheduled Tasks](scheduled_tasks.md)
28	- Recurring automation workflows
29	- Pattern: Schedule → Fetch → Process → Deliver → Log
30
31	6. Batch Processing (below)
32	- Process large datasets in chunks with API rate limits
33	- Pattern: Prepare → SplitInBatches → Process per batch → Accumulate → Aggregate
34
35	---
36
37	## Pattern Selection Guide
38
39	### When to use each pattern:
40
41	Webhook Processing - Use when:
42	- Receiving data from external systems
43	- Building integrations (Slack commands, form submissions, GitHub webhooks)
44	- Need instant response to events
45	- Example: "Receive Stripe payment webhook → Update database → Send confirmation"
46
47	HTTP API Integration - Use when:
48	- Fetching data from external APIs
49	- Synchronizing with third-party services
50	- Building data pipelines
51	- Example: "Fetch GitHub issues → Transform → Create Jira tickets"
52
53	Database Operations - Use when:
54	- Syncing between databases
55	- Running database queries on schedule
56	- ETL workflows
57	- Example: "Read Postgres records → Transform → Write to MySQL"
58
59	AI Agent Workflow - Use when:
60	- Building conversational AI
61	- Need AI with tool access
62	- Multi-step reasoning tasks
63	- Example: "Chat with AI that can search docs, query database, send emails"
64
65	Scheduled Tasks - Use when:
66	- Recurring reports or summaries
67	- Periodic data fetching
68	- Maintenance tasks
69	- Example: "Daily: Fetch analytics → Generate report → Email team"
70
71	Batch Processing - Use when:
72	- Processing large datasets that exceed API batch limits
73	- Need to accumulate results across multiple API calls
74	- Nested loops (e.g., multiple categories × paginated API calls per category)
75	- Example: "Fetch products for 4 markets × 1000 per API call → Aggregate all results"
76
77	---
78
79	## Common Workflow Components
80
81	All patterns share these building blocks:
82
83	### 1. Triggers
84	- Webhook - HTTP endpoint (instant)
85	- Schedule - Cron-based timing (periodic)
86	- Manual - Click to execute (testing)
87	- Polling - Check for changes (intervals)
88
89	### 2. Data Sources
90	- HTTP Request - REST APIs
91	- Database nodes - Postgres, MySQL, MongoDB
92	- Service nodes - Slack, Google Sheets, etc.
93	- Code - Custom JavaScript/Python
94
95	### 3. Transformation
96	- Set - Map/transform fields
97	- Code - Complex logic
98	- IF/Switch - Conditional routing
99	- Merge - Combine data streams
100
101	### 4. Outputs
102	- HTTP Request - Call APIs
103	- Database - Write data
104	- Communication - Email, Slack, Discord
105	- Storage - Files, cloud storage
106
107	### 5. Error Handling
108	- Error Trigger - Catch workflow errors
109	- IF - Check for error conditions
110	- Stop and Error - Explicit failure
111	- Continue On Fail - Per-node setting
112
113	---
114
115	## Workflow Creation Checklist
116
117	When building ANY workflow, follow this checklist:
118
119	### Planning Phase
120	- [ ] Identify the pattern (webhook, API, database, AI, scheduled)
121	- [ ] List required nodes (use search_nodes)
122	- [ ] Understand data flow (input → transform → output)
123	- [ ] Plan error handling strategy
124
125	### Implementation Phase
126	- [ ] Create workflow with appropriate trigger
127	- [ ] Add data source nodes
128	- [ ] Configure authentication/credentials
129	- [ ] Add transformation nodes (Set, Code, IF)
130	- [ ] Add output/action nodes
131	- [ ] Configure error handling
132
133	### Validation Phase
134	- [ ] Validate each node configuration (validate_node)
135	- [ ] Validate complete workflow (validate_workflow)
136	- [ ] Test with sample data
137	- [ ] H

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n8n-workflow-patterns

8.9kinstalls983forks

View on GitHub

How to install n8n-workflow-patterns?

czlonkowski/n8n-skills/n8n-workflow-patterns

$npx -y skills add czlonkowski/n8n-skills --skill n8n-workflow-patterns

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# n8n Workflow Patterns
2
3	Proven architectural patterns for building n8n workflows.
4
5	---
6
7	## The 6 Core Patterns
8
9	Based on analysis of real workflow usage:
10
11	1. [Webhook Processing](webhook_processing.md) (Most Common)
12	- Receive HTTP requests → Process → Output
13	- Pattern: Webhook → Validate → Transform → Respond/Notify
14
15	2. [HTTP API Integration](http_api_integration.md)
16	- Fetch from REST APIs → Transform → Store/Use
17	- Pattern: Trigger → HTTP Request → Transform → Action → Error Handler
18
19	3. [Database Operations](database_operations.md)
20	- Read/Write/Sync database data
21	- Pattern: Schedule → Query → Transform → Write → Verify
22
23	4. [AI Agent Workflow](ai_agent_workflow.md)
24	- AI agents with tools and memory
25	- Pattern: Trigger → AI Agent (Model + Tools + Memory) → Output
26
27	5. [Scheduled Tasks](scheduled_tasks.md)
28	- Recurring automation workflows
29	- Pattern: Schedule → Fetch → Process → Deliver → Log
30
31	6. Batch Processing (below)
32	- Process large datasets in chunks with API rate limits
33	- Pattern: Prepare → SplitInBatches → Process per batch → Accumulate → Aggregate
34
35	---
36
37	## Pattern Selection Guide
38
39	### When to use each pattern:
40
41	Webhook Processing - Use when:
42	- Receiving data from external systems
43	- Building integrations (Slack commands, form submissions, GitHub webhooks)
44	- Need instant response to events
45	- Example: "Receive Stripe payment webhook → Update database → Send confirmation"
46
47	HTTP API Integration - Use when:
48	- Fetching data from external APIs
49	- Synchronizing with third-party services
50	- Building data pipelines
51	- Example: "Fetch GitHub issues → Transform → Create Jira tickets"
52
53	Database Operations - Use when:
54	- Syncing between databases
55	- Running database queries on schedule
56	- ETL workflows
57	- Example: "Read Postgres records → Transform → Write to MySQL"
58
59	AI Agent Workflow - Use when:
60	- Building conversational AI
61	- Need AI with tool access
62	- Multi-step reasoning tasks
63	- Example: "Chat with AI that can search docs, query database, send emails"
64
65	Scheduled Tasks - Use when:
66	- Recurring reports or summaries
67	- Periodic data fetching
68	- Maintenance tasks
69	- Example: "Daily: Fetch analytics → Generate report → Email team"
70
71	Batch Processing - Use when:
72	- Processing large datasets that exceed API batch limits
73	- Need to accumulate results across multiple API calls
74	- Nested loops (e.g., multiple categories × paginated API calls per category)
75	- Example: "Fetch products for 4 markets × 1000 per API call → Aggregate all results"
76
77	---
78
79	## Common Workflow Components
80
81	All patterns share these building blocks:
82
83	### 1. Triggers
84	- Webhook - HTTP endpoint (instant)
85	- Schedule - Cron-based timing (periodic)
86	- Manual - Click to execute (testing)
87	- Polling - Check for changes (intervals)
88
89	### 2. Data Sources
90	- HTTP Request - REST APIs
91	- Database nodes - Postgres, MySQL, MongoDB
92	- Service nodes - Slack, Google Sheets, etc.
93	- Code - Custom JavaScript/Python
94
95	### 3. Transformation
96	- Set - Map/transform fields
97	- Code - Complex logic
98	- IF/Switch - Conditional routing
99	- Merge - Combine data streams
100
101	### 4. Outputs
102	- HTTP Request - Call APIs
103	- Database - Write data
104	- Communication - Email, Slack, Discord
105	- Storage - Files, cloud storage
106
107	### 5. Error Handling
108	- Error Trigger - Catch workflow errors
109	- IF - Check for error conditions
110	- Stop and Error - Explicit failure
111	- Continue On Fail - Per-node setting
112
113	---
114
115	## Workflow Creation Checklist
116
117	When building ANY workflow, follow this checklist:
118
119	### Planning Phase
120	- [ ] Identify the pattern (webhook, API, database, AI, scheduled)
121	- [ ] List required nodes (use search_nodes)
122	- [ ] Understand data flow (input → transform → output)
123	- [ ] Plan error handling strategy
124
125	### Implementation Phase
126	- [ ] Create workflow with appropriate trigger
127	- [ ] Add data source nodes
128	- [ ] Configure authentication/credentials
129	- [ ] Add transformation nodes (Set, Code, IF)
130	- [ ] Add output/action nodes
131	- [ ] Configure error handling
132
133	### Validation Phase
134	- [ ] Validate each node configuration (validate_node)
135	- [ ] Validate complete workflow (validate_workflow)
136	- [ ] Test with sample data
137	- [ ] H

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6 picks

Type