Tools, APIs, Structured Outputs, and Agent Runtime Design
Tool use as computation
From text to action
Tool use turns natural language into an action interface: the model emits structured requests, the runtime executes them, and observations are fed back into the loop. OpenAI’s 2025 agents stack highlighted the Responses API, hosted tools, structured outputs, and tracing as the building blocks of agent systems. ([help.openai.com](https://help.openai.com/en/articles/8555517-function-calling-in-the-openai-api%23.otf?utm_source=openai))
Why structure matters
Structured outputs reduce parsing ambiguity and make tool calls easier to validate, while tracing supports debugging, evaluation, and postmortem analysis. ([help.openai.com](https://help.openai.com/en/articles/8555517-function-calling-in-the-openai-api%23.otf?utm_source=openai))
Runtime components
Safety note
Tool-using agents can turn prompt injection, bad schemas, or weak permissions into concrete external harm.
Why are JSON schemas and structured outputs important for agents?
Structured outputs improve reliability at the interface between model and environment.
Correct answer: They ensure tool arguments can be validated and parsed reliably
What is tracing mainly used for in agent systems?
Tracing makes agent trajectories inspectable and measurable.
Correct answer: Debugging, evaluation, and monitoring execution trajectories
Give one reason to separate planner and executor roles.
Separating concerns can reduce coupling between high-level intent and low-level execution.
Correct answer: Modularity and safer control
What is one risk of exposing too many tools to an agent?
More tools can increase prompt injection, privilege misuse, and accidental actions.
Correct answer: Expanded attack surface