Verified80% confidenceFactExact time
The 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.
4
Sources
80%
Confidence
Long-term
Relevance
7/12/2026
First Seen
Sources
Prismata Analysis: How to Defend Web Agents Against Cross-Site Prompt Injection Attacks
hackernewshackernews7/10/2026
Related Claims
VerifiedUnder the tool-calling paradigm, the LLM outputs a structured function-call intent (in JSON format), which is actually executed by an external system that returns the result to the model.84% similarVerifiedFunction 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83% similarVerifiedIn 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% similarUnverifiedLLM本身并不直接执行工具，而是生成一个JSON字符串指定要调用的工具名和参数，由Agent执行逻辑解析并实际调用对应函数81% similarVerifiedTools are essentially function wrappers for external capabilities, paired with JSON Schema descriptions that enable the model to understand a tool's functionality and parameter format.79% similar
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