Problems / Multi-agent and harness, hard
Eight subagents each call a tool that fails 1% of the time; any subagent failure fails the question.
Free to open. Runs in your browser, no sign-up.
Success ≥ 95% of tasks, p99 ≤ 90 s.
8 requests a second for 45 seconds: 100% task (writes).
What each component does in this design, and what calls it. The simulator mimics each one from these settings.
| Component | Its job here | Settings |
|---|---|---|
| Load balancerLoad balancer | Traffic enters here.Calls Agent API.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header. | – |
| Agent APIApp service | Load balancer forwards to it.Calls Agent orchestrator.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s. | 3 replicas × 500 slots · timeout 180 s |
| Agent orchestratorAgent orchestrator | Agent API calls it.Calls Subagent pool.An agent loops: think, call a tool, read the result, repeat until done. | 400 slots · 1 steps |
| Subagent poolSubagent pool | Agent orchestrator calls it.Calls MCP tool servers.Multi-agent research systems fan a task out to parallel subagents and use many times more tokens than a single agent. | 400 slots · 8 steps |
| MCP tool serversTool / MCP server | Subagent pool calls it.Tools give the model actions such as search or database queries; each call is another round trip. | 200 slots |
Try it first. Open one hint at a time if you get stuck.
1 − 0.99⁸ ≈ 8%.
Fewer, better-scoped subagents.
Reduce the fan-out.