OpenAI Agents SDK

Writing the loop yourself gets old quickly: call the model, parse the tool request, run the function, append the result, call again, and somewhere in there decide when to stop. The OpenAI Agents SDK is OpenAI's own answer to that chore — a small Python (and TypeScript) library that runs the loop for you.

What it gives you
The design is deliberately thin — a handful of primitives rather than a framework to learn:

• Agents: a model, instructions, and a list of tools. Plain functions become tools from a decorator, their schema read off the type hints.
• Handoffs: one agent passes control to another — a triage agent routing to a billing specialist — which is how multi-agent work is expressed here, instead of a message bus.
• Guardrails: validation that runs alongside the agent and can halt it early on an unsafe or out-of-scope input.
• Sessions and tracing: conversation history carried across turns, and every run viewable step by step in the OpenAI dashboard.

Why it matters
It is the production successor to the experimental Swarm project, and it collapses the run-time plumbing — retries, step limits, structured output, trace spans — behind a single Runner.run() call. The trade-off is the familiar one: a lean, readable agent at the price of a loop you no longer own. Where the step cap lives, how a handoff rewrites the context the next agent sees, and what a guardrail does to an in-flight run are all worth knowing before a deployed agent surprises you.