Problems / Multi-agent and harness, medium

Harness compaction backs up

The harness compacts context on every turn with a summariser that has 4 slots.

Free to open. Runs in your browser, no sign-up.

Your goals

Success ≥ 95% of tasks, p99 ≤ 90 s.

The traffic

3 requests a second for 45 seconds: 100% task (writes).

The system

What each component does in this design, and what calls it. The simulator mimics each one from these settings.

ComponentIts job hereSettings
Load balancerLoad balancerTraffic 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 serviceLoad balancer forwards to it.Calls Agent harness.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 harnessAgent harnessAgent API calls it.Calls Model, Context compactor.A harness is everything around the model in an agent: context management, tools, checkpoints, retries and evaluation.400 slots · 6 steps
ModelLLM endpointAgent harness calls it.Latency has two parts: time to the first token, then a steady stream of tokens per second.1000 streams
Context compactorContext compactorAgent harness calls it.Compaction summarises a long context so the agent can keep going without hitting the window limit.4 slots

Hints

Try it first. Open one hint at a time if you get stuck.

Hint 1

Compact when the window is nearly full, not every turn.

Hint 2

Multiply by the fan-out and the number of turns to get the real call rate on shared models and tools.

One way to solve it

Give the compactor more capacity.

More multi-agent and harness problems