Hello everyone,
I’m currently developing custom nodes and am particularly interested in the AI-powered workflow generation capabilities in n8n. I’d like to understand how to structure my custom nodes to optimally support automatic workflow creation via AI.
Specifically, I’m looking for guidance on:
Node metadata and descriptions - How should I configure the INodeTypeDescription to make my nodes more discoverable and understandable for the AI Workflow Builder? The documentation mentions that node definitions and parameters are sent to the LLM, so I want to optimize these for AI comprehension.
Parameter naming and documentation - Are there best practices for writing descriptions, parameter names, and documentation that AI can effectively parse and understand?
Using nodes as AI Agent tools Are there additional considerations for making custom nodes work seamlessly as AI Agent tools?
Data flow optimization - How should I structure node inputs and outputs so that the AI can better understand and orchestrate the data flow?
Additionally, I’m curious: Can I leverage the same AI engine that n8n uses for workflow generation within my custom node logic? Is there an API or internal service I can access to integrate AI capabilities directly into my nodes?
I want to build my nodes in a way that integrates seamlessly with n8n’s AI features from day one. Are there any resources, deep documentation, or community patterns I should be aware of?
Thanks in advance for your insights!