Writing Tools for Agents: The ACI Is as Important as the API
Most engineers approach agent tools the same way they approach writing a REST endpoint or a library function: expose the capability cleanly, document the parameters, handle errors. That's the right instinct for humans. For AI agents, it's exactly wrong.
A tool used by an agent is consumed non-deterministically, parsed token by token, and selected by a model that has no persistent memory of which tool it used last Tuesday. The tool schema you write is not documentation — it is a runtime prompt, injected into the model's context at inference time, shaping every decision the agent makes. Every field name, every description, every return value shape is a design decision with measurable performance consequences. This is the agent-computer interface (ACI), and it deserves the same engineering investment you'd put into any critical user-facing interface.
