Most agent frameworks force a tradeoff: powerful orchestration buried under heavy abstractions, or thin wrappers that leave you wiring everything by hand. This SDK bets that two primitives — agents and handoffs — are enough to express most multi-agent systems, and that the real work is making that small surface debuggable in production.
The insight is treating delegation as a first-class control flow. Instead of one mega-prompt juggling every responsibility, you define focused agents and let one hand off to another the way a triage desk routes a ticket. The runtime loop, tool calls, and conversation state are handled for you, so the code reads like the org chart of the problem.
What Sets It Apart
- Handoffs as routing: specialized agents delegate to each other, keeping each prompt small and testable rather than one brittle monolith.
- Provider-agnostic: runs on OpenAI's models or 100+ others through a common interface, so model choice stays a config decision, not a rewrite.
- Guardrails run alongside execution to validate inputs and outputs, catching bad calls before they reach a tool or user.
- A built-in tracing UI visualizes each run — every handoff, tool call, and guardrail — which is usually the missing piece when multi-agent flows misbehave.
Who It's For
Great fit if you're building agentic systems in Python and want orchestration plus first-class observability without adopting a large framework — especially teams already in the OpenAI ecosystem who still want model portability. Look elsewhere if you need a no-code/visual builder, work outside Python, or your task is a single tool-calling prompt where an agent loop and handoffs add more machinery than the problem warrants.
