Verified65% confidenceFactExact time
The Tool Routing mechanism selects tools by performing similarity matching between the semantic representation of user intent and the embedding vectors of tool descriptions, so the quality of a tool's natural language description directly affects the agent's decision-making accuracy.
3
Sources
65%
Confidence
Long-term
Relevance
7/21/2026
First Seen
Sources
Related Claims
UnverifiedThe tool routing mechanism first uses embedding vector retrieval or a classifier to pre-judge user intent, narrowing the candidate tool pool to 3–5 options, which are then passed to the LLM for precise selection, similar to the recall-ranking two-stage architecture of a search engine.77% similarUnverifiedThe tool-calling capability of intelligent agents allows language models to determine whether a tool needs to be called, generate call parameters conforming to the API specification, and continue reasoning based on the execution results.75% similarUnverified工具调用能力的关键突破在于模型能生成结构化函数调用请求并正确解析工具返回结果后继续推理，而非简单将工具输出拼接进提示词74% similarVerifiedThe Tool Use protocol introduced by Anthropic excels in parallel multi-tool invocation and nested tool chains.73% similarVerifiedThe quality of a tool's description directly determines whether the model can select the correct tool; vague descriptions cause the model to call the wrong tool or pass incorrect parameters.73% similar
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