Tool Selection: How the LLM Decides When and Which Tool to Call
~15 min read
The LLM picks a tool by reading its name and description against the current task — which means prompt/description design directly determines whether the right tool gets called at the right time.
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Key points
- •The model decides whether/which tool to call by matching each tool's name and description against the current request
- •Tool selection quality is almost entirely a function of description quality, not the underlying implementation
- •More tools doesn't mean better results — unnecessary or overlapping tools confuse selection and reduce efficiency
- •Descriptions should specify WHEN to use a tool, not just what it does
- •Keep the active tool list scoped to what's genuinely relevant for the current context, not every tool ever defined