How do you design tool definitions so an LLM agent uses them correctly?

What the interviewer wants to hear

• Clear names and descriptions with when to use and not use
• Typed parameter schemas with formats and examples
• Few, non-overlapping tools
• Informative results and error messages
• Evaluate tool choice and arguments on test tasks

Model answer

The model only sees a tool's name, description and parameter schema, so I write them like good API docs for a new colleague. Each description says what the tool does, when to use it and when not to, and what it returns. Parameters have clear names, types, enums where possible, formats such as ISO dates, and short examples. I keep the set small and avoid overlapping tools; if two tools could both answer the same question, the model will pick inconsistently, so I merge them or sharpen the boundary. Results should be concise and relevant, not huge raw dumps, and errors should explain what went wrong so the model can retry correctly. Finally I build test tasks that check whether the agent chooses the right tool with valid arguments, and I read traces to find confusion.

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