Free tool / decision quiz

Do You Need Multiple Agents?

Answer six architecture questions and get a verdict: keep one well-tooled agent, use a fixed workflow, or prototype a multi-agent system with a specific orchestration pattern.

Architecture questions

Pick the closest answer for each dimension. The scoring intentionally penalizes vague splits that add agents without improving evaluation, context, or tool ownership.

Can the task split into independent work?
How much context does the task need?
Do roles need different tools or policies?
Would independent verification improve quality?
How tight are latency and cost constraints?
How tightly coupled are the decisions?

How the score works

The quiz adds points for task breadth, separate context, role-specific tools, verifiable intermediate artifacts, and enough value to tolerate extra latency. It subtracts points for tight coupling, low budget, and evaluation ambiguity. That mirrors the sourced debate: multi-agent systems can add real capacity, but they also multiply coordination surfaces.

Is this quiz a substitute for evals?

No. It is a screening tool. Use the result to decide what prototype to test, then compare a single-agent baseline against the recommended split on real tasks.

What score means I should use multiple agents?

Scores above six suggest a multi-agent prototype may be worth testing. Scores below three usually point to one agent or a fixed workflow first.

Why does latency reduce the multi-agent score?

More agents usually mean more model calls, more coordination, and more waiting. A low-latency task needs unusually strong quality upside to justify that overhead.

Does a high score mean a swarm is right?

Usually no. Most high-scoring tasks start with orchestrator-worker, pipeline, handoff, or judge-panel designs before anything as loose as a swarm.

Read next

Single vs multi decision guide

The sourced version of the same architecture decision.

Pattern picker

Choose the pattern after the quiz says a split may be justified.

Cost estimator

Check whether the recommended split is economically reasonable.

Sources used on this page

Anthropic / 2024-12-19

Building effective agents

Defines workflows vs agents and recommends starting with the simplest solution that meets the task.

Anthropic / 2025-06-13

How we built our multi-agent research system

Concrete pro case for breadth-first research, with reported 90.2% internal eval gain and about 15x chat token use.

Cognition / 2025-06-12

Don't Build Multi-Agents

Argues that parallel agents are fragile when context and implicit decisions are not shared thoroughly.

OpenAI / 2025

A practical guide to building agents

Recommends maximizing one agent first, then splitting for prompt complexity, tool overload, manager patterns, or handoffs.