🤖 AI EngineeringID:
function-calling-protocolFunction Calling Protocol
Function Calling 协议与参数注入
🎯Core Definition
Function Calling Protocol (Tool Use API) is the standardized industrial interface enabling LLMs to interact deterministically with external software environments; developers provide a `tools` list containing JSON Schema definitions (function `name`, functional `description`, and strict typing/required `parameters`); the LLM autoregressively determines tool invocation requirements, yielding a structured tool execution payload: `tool_calls: [{id: 'call_abc123', function: {name: 'get_weather', arguments: '{"city": "Tokyo"}'}}]` while pausing generation for host execution.
💡Use Cases
Real-time SQL database queries, transactional external API actions, flight booking workflows, and foundational action channels in Autonomous Agents.
⚡Key Problems Solved
Relying on raw natural language prompt engineering for tool outputs regularly yields malformed syntax, missing parameters, or type mismatches; native Function Calling embeds specialized training tokens to enforce bulletproof JSON argument emission.
🎯5 High-Frequency Exam Points
1
Detail the control logic of `tool_choice` modes (`'auto'`, `'none'`, `'required'`, or forcing a specific function)?
2
How does the model inference runtime serialize JSON Schema tool definitions into system prompt / hidden context representations?
3
Analyze how the precision and clarity of function `description` texts dictate LLM Tool Selection Accuracy under tool ambiguity?
4
How to use Semantic Tool Search / Tool Routers to dynamically inject only the top-5 relevant tools when managing 50+ tools?
5
Compare Anthropic Claude's native XML tool use syntax vs OpenAI's JSON Schema function calling schema?
📖 In-depth Guide:📄 tool-use-and-function-calling →
Updated 2026-08-14🎯
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