Key parameters to tune
All of these live insideMyAgent in the notebook:
MAX_ACTIONS(e.g.50) — the number of actions the agent takes per game. This is the single best knob to tune.MESSAGE_LIMIT(e.g.2) — how many past steps are sent to the model. We keep this low (2) because the context window fills up quickly with the JSON grid for each frame.GAME_TIME_LIMIT_S— the per-game time limit. Keep this low. If it’s too high you’ll hit ascorecard not produced in timeerror, which fails the run.MAX_MODEL_LEN— the model’s context length.build_user_prompt— the function that assembles the prompt sent to the model. Fun to experiment with for better guidance.
Test locally on one game
Before submitting, confirm a single game runs end-to-end:- Use Save & Run All (Commit) to run the notebook end-to-end in local mode.
Submit to the competition
(Optional) Run All for quick experiments
If you don’t need to save a version, just use Run All. This is quicker-ish than a save and commit and is handy for iterating on experiments.
Save & Run All (Commit)
Once you’re happy with an intermediate result, use Save & Run All (Commit) and give it a clear version name.

