You are designing the prompt for a ticket-triage classifier with thirty well-defined categories and clear...

A clearly defined closed-set classification task should begin with a concise zero-shot prompt containing the permitted categories, unambiguous category descriptions, and the required output structure. This provides a simple, inexpensive baseline that can be measured against a representative evaluation set. Chain-of-thought prompting adds unnecessary latency and token usage when the routing decision does not require substantive multi-step reasoning. Permitting Claude to invent categories would violate the closed-set contract and complicate downstream automation. Omitting descriptions would increase ambiguity among potentially overlapping labels. If evaluation later reveals persistent confusion between particular categories, the architect can introduce targeted examples or refine the definitions. Prompt complexity should be added in response to measured failure patterns, not assumed to be necessary before establishing baseline performance. Anthropic: Prompt engineering overview

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