What are the best practices for designing AI agent tool interfaces?

Well-designed tool interfaces are critical for agent effectiveness. Each tool should have a clear, descriptive name that indicates its purpose. Parameter descriptions should be detailed enough for the LLM to understand when and how to use each parameter. Use specific types rather than generic strings, for example an enum for status values rather than a free-text field. Provide parameter validation with clear error messages explaining what went wrong and how to fix it. Return structured responses with consistent schemas. Include relevant context in return values that helps the agent reason about next steps. Limit the number of tools to what the agent actually needs since too many tools increase decision complexity and errors. Group related operations logically. Design tools to be atomic, performing one clear action per call. Include confirmation or preview tools for destructive operations. Version tool interfaces to maintain backward compatibility. Document common usage patterns and edge cases in tool descriptions.