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How to compare local decision models with stuntdouble with Jevbench

Use the independent stuntdouble companion to import JevBench public hard items and compare local models.

  • Research
  • Intermediate
  • 1 hour
  • From the README
  • Any agent

Who it is forA developer running local decision models who wants a side-by-side comparison on the same public items.

The problemLocal model tests are hard to repeat and compare when every setup uses different items and tooling.

The outcomeA replay of the same public JevBench hard items across your local decision models, with a report you can rerun.

What you need first

  • A web browser to read the public boards and release manifest
  • Git and Python for the local repo steps
  • Your decision model reachable from your own machine if you run the option-order test

Steps

  1. Open the stuntdouble project at https://github.com/ReallyArtificial/stuntdouble and read its setup notes.
  2. Confirm that stuntdouble can import JevBench's public hard items, as the README describes.
  3. Import the public hard items from the JevBench repo into stuntdouble.
  4. Run each local decision model through the import and record the results for each one.
  5. Write up the comparison and label it as your own result, since stuntdouble is not a JevBench entrant and its example report is not an official JevBench result.

Prompt for your agent

Read the stuntdouble project at github.com/ReallyArtificial/stuntdouble and import the public hard items from github.com/fstandhartinger/jevbench (datasets/public/hard.jsonl) to compare <list of local decision models>. Output a table of results per model and a note that these are not official JevBench results. Verify that the import used only the public split.

Caveat. stuntdouble is a third-party tool, and its example report is not an official JevBench result, so cite it only as your own comparison.

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