Verified80% confidenceFactTime unknown
Function Calling机制中，开发者将工具的名称、功能描述、参数Schema（通常为JSON Schema格式）注入到模型的请求中，模型输出结构化的JSON而非自然语言来调用工具
33
Sources
80%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
Agent智能体工作原理拆解：四要素与ReAct循环决策机制详解
bilibili大模型小阳
Related Entities
Related Claims
UnverifiedThe underlying implementation of tool calling typically relies on the Function Calling protocol, where developers describe a tool's name, parameter types, and semantics in JSON Schema format, and the model outputs structured invocation instructions conforming to the protocol format.83% similarUnverifiedThe Function Calling mechanism allows LLMs to declare in structured JSON format the external tools and parameters they need to invoke, and the tool's return value is injected as-is into the next round of model input.83% similarUnverifiedThe core mechanism of Function Calling is that developers describe external function signatures in JSON Schema format, and the model outputs structured JSON invocation instructions that conform to the schema specification.82% similarUnverifiedIn the tool-calling mechanism, developers attach a tool description list in JSON Schema format when calling the LLM API, and the model outputs call parameters in structured JSON format82% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/16553API
curl https://kongchang.com/api/v1/knowledge/claims/16553MCP
get_claim(id=16553)