How do I choose the right pattern for my automation?

The skill includes a Pattern Selection Guide that maps specific triggers (like Stripe payments or recurring reports) to the most efficient architectural structure.

Can this skill help me fix n8n error handling?

Yes, it provides specific strategies for using Error Triggers, 'Continue On Fail' settings, and specialized error-handling workflow branches.

Does it provide guidance on n8n expression syntax?

While it focuses on architecture, it includes specific 'Gotchas' and best practices for accessing webhook data and using the correct expression syntax in transformation nodes.

Is this compatible with n8n AI nodes?

Absolutely. It features a dedicated AI Agent Workflow pattern that covers the integration of Language Models, Tools, and Memory within the n8n ecosystem.

n8n Workflow Architect

Name: n8n Workflow Architect
Author: ProfSynapse

byProfSynapse

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Productivity & Workflow

Provides proven architectural patterns and best practices for building robust, scalable n8n automation workflows.

About

This skill empowers developers to design and implement sophisticated n8n workflows by leveraging five core architectural patterns: Webhook Processing, HTTP API Integration, Database Operations, AI Agent Workflows, and Scheduled Tasks. It offers a structured approach to automation, providing expert guidance on node selection, data transformation logic, error handling strategies, and deployment checklists. Whether you are building a simple notification system or a complex AI-driven agentic workflow, this skill ensures your n8n builds follow industry best practices for reliability and maintainability.

Key Features

Detailed implementation and validation checklists for every workflow phase
Specialized guidance for building AI Agent workflows with tools and memory
Best practices for complex data transformation and error handling
Standardized architectural patterns for the 5 most common n8n use cases
40 GitHub stars
Optimized data flow patterns including Branching, Looping, and Parallel processing

Use Cases

Designing a high-volume webhook processing system with payload validation
Architecting complex AI agents that utilize external tools and persistent memory
Building reliable ETL and data synchronization pipelines between disparate databases

About

Key Features

Detailed implementation and validation checklists for every workflow phase
Specialized guidance for building AI Agent workflows with tools and memory
Best practices for complex data transformation and error handling
Standardized architectural patterns for the 5 most common n8n use cases
40 GitHub stars
Optimized data flow patterns including Branching, Looping, and Parallel processing

Use Cases

Designing a high-volume webhook processing system with payload validation
Architecting complex AI agents that utilize external tools and persistent memory
Building reliable ETL and data synchronization pipelines between disparate databases