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run-an-agent-team

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Design a small team of AI agents to tackle a complex task in parallel — who does what, how they hand off, and how to keep them coordinated — instead of one overloaded agent doing everything serially. Use when asked how do I use multiple AI agents, set up an agent team, orchestrate agents for, or run agents in parallel. Produces a decomposition of the task into agent roles, a coordination pattern (parallel vs sequential, how outputs combine), the context each agent needs (and what to keep isolated), a review/quality step, and the guardrails to keep it from going off the rails — practical multi-agent design for real tasks.

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# Run an Agent Team

Complex tasks overwhelm a single AI agent — the context gets muddy, quality drops, and it does everything serially. A small team of specialized agents, each with a focused role and clean context, can tackle it in parallel and check each other's work. This designs that team for your task: the roles, how they coordinate and hand off, what context each needs (and what to isolate), and the guardrails — turning "one agent doing everything" into a coordinated effort.

## What This Skill Produces

- **The task decomposition** — the task broken into distinct agent roles, each with a focused responsibility (researcher, drafter, critic, integrator, etc.)
- **A coordination pattern** — whether agents run in parallel or sequence, how their outputs combine, and where the hand-offs are
- **Context design** — what each agent needs to know, and (crucially) what to keep *isolated* so one agent's context doesn't muddy another's (the key to why teams beat one agent)
- **A review/quality step** — a separate agent or pass to critique and integrate, so quality is checked, not assumed
- **Guardrails** — how to keep the team on track (clear objectives, defined outputs, a human checkpoint) and avoid runaway loops or drift
- **A right-sized recommendation** — including when a single agent is genuinely better (not everything needs a team)

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