Implementing tool calling with strict JSON schemas for agents typically starts by defining each tool's precise JSON schema, detailing expected parameter types, descriptions, and required fields. This schema is then provided to the agent, usually within its system prompt, allowing the LLM to understand the correct syntax and arguments for available functions. When the agent generates a tool call, its output is immediately subjected to rigorous schema validation against the predefined JSON schema for the target tool. This critical step ensures that all parameters conform to their specified types and constraints, preventing malformed or invalid invocations. Only upon successful validation, guaranteeing schema-compliant arguments, is the tool executed. If validation fails, an error is typically raised, prompting the agent for correction or signaling a failure, ensuring robust and predictable agent behavior. More details: https://www.hikari-mitsushima.com/refsweep.cgi?https://infoguide.com.ua/