Originally published on AI Tech Connect.
Why tool selection fails Tool calling is the primitive that turns a language model into an agent. Give the model a list of callable functions, and it can query databases, trigger APIs, read files, and execute code — all from natural-language instructions. In theory, the model reads a tool description, decides whether it is appropriate, and emits a structured call. In practice, the failure modes are numerous and frustrating to diagnose. The root cause in the majority of cases is not model quality — it is schema quality. Three specific problems account for most tool-selection failures in production agents. Vague descriptions. A tool described only as "Gets information about a user" gives the model no signal about when to use it versus a similarly vague "Fetches user details" tool. The model…