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How to measure run time, model cost and memory of a city with Sprawling Agents

Read timings, tokens, cost and resource use with gauge and set a memory ceiling.

Who it is forA developer on a shared or limited machine who needs to know what an agent team costs in tokens and memory.

The problemLong runs can use model budget and memory without showing where it went.

The outcomeA report of run timings, model calls, tokens, cost and resource use on your hardware, with a memory limit you chose.

What you need first

  • Node.js and npm for the npm install route, or Bun, or the Rust toolchain for cargo install
  • A model provider account you can connect, or a local model
  • A browser to use the page the city opens
  • Alpha software: data formats and the interface may change between versions

Steps

  1. Start the city with sprawling up ./cities/first and run a short task.
  2. Run sprawling gauge to read timings, model calls, tokens, cost and resource use.
  3. Open Settings → Performance and set a memory ceiling for each run if you want one.
  4. Compare the readings with the budgets in tools/xtask/budgets.toml.

Prompt for your agent

In the 2youg1/sprawling-agents repo, run a short task in a city at ./cities/first, then run `sprawling gauge` and save its output. Expected output: a summary of run timings, tokens and cost. Verify that the figures are from your own machine, not from the recorded readings in tools/xtask/budgets.toml.

Caveat. The README says there is no memory ceiling by default and only you can set one, so runs have no limit until you choose one.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for 2youg1/sprawling-agents and "Measure run time, model cost and memory of a city"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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