In this article, you will learn how tool design — not model capability — is the root cause of most AI agent failures, and what concrete design patterns you can apply to fix it.
Topics we will cover include:
Tool design practices that improve agent reliability, including single-responsibility tools, tight schemas, and structured error returns.
Common failure modes such as unfiltered API exposure, silent partial success, and overlapping tool names that break real-world workloads.
Schema and error handling patterns that reduce hallucination and unreliable behavior at the tool boundary.
