Four Design Principles That Stop LLMs From Misusing Agent Tools

A software engineer writing for DEV Community argues that most bugs in LLM-based agents originate not in the model itself but in poorly designed tool schemas. Because a language model can only infer how a tool works from its parameter names, types, and descriptions, ambiguous schemas cause the model to guess incorrectly and misuse the tool. The author identifies four properties that make tools harder to misuse: a legible schema, a validating boundary, recoverable errors, and idempotency. Practical examples show how replacing vague field types with enums, adding numeric bounds, and writing precise descriptions can eliminate entire categories of invalid inputs. The core recommendation is to treat the schema as the complete specification, since the model has no access to source code or external documentation.