This n8n workflow automates the creation, validation, and testing of custom JSON formats for AI agents. Starting with a manual trigger, it generates an initial JSON structure based on a given scenario, then iteratively refines this structure through validation and testing nodes. Using custom nodes like ‘JSON Generator’ and ‘Advanced JSON Output Parser,’ the workflow ensures the JSON format accurately matches the intended use case, such as in conversational AI or data integration tasks. If the generated JSON is invalid or fails tests, the process loops until a valid format is achieved or a maximum number of rounds is reached. This workflow is valuable for developers and AI trainers who need to create reliable, scenario-specific JSON schemas dynamically, streamlining the integration of AI with structured data formats.

Node Count	>20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmChatMistralCloud, @n8n/n8n-nodes-langchain.outputParserStructured, if, manualTrigger, n8n-nodes-advanced-output-parser.advancedOutputParser, noOp, set, splitInBatches, stickyNote, stopAndError