Digbench-Runs
Run traces for the EWM harness (schema world-model harness) and a basic harness on DiG-bench,
model gpt-6-astra via Codex, 21 games (P-1 … P-21) at three reasoning levels (medium, high, max).
Layout
index.csv— one row per (game, reasoning level, harness). Columns:game, tier, reasoning, harness, levels_beaten, max_level, won, steps, path, source.pathpoints into this dataset;sourceis the original local path the run came from.ewm/<reasoning>/P-<n>/— one EWM run per directory:events.jsonl(full event trace),run.json(run config),notes.md,sessions/,snapshots/, plus the world-model / planner code the agent wrote during the run.git.tar.gzholds the run's own git repository (one commit per turn, tagsstartandcleared_level_<k>). Restore it withcd ewm/<reasoning>/P-<n> && tar xzf git.tar.gz; the working tree then matches the files in this directory (events.jsonlcarries the finalrun_finishedline as an uncommitted change, as the harness leaves it).basic/<reasoning>/P-<n>.jsonl— the basic-harness run for the same game and reasoning level.
events.jsonl
One JSON object per line with a kind field: run_started, turn_started (observation, level, lives,
steps remaining, surprise), thinking_delta, tool_started (name, args, call_id),
tool_finished (output, is_error, call_id), turn_committed (plan, reason, usage),
turn_fallback, action_taken (action, observation, level, levels_beaten, level_up, win, …),
model_mispredicted (predicted vs actual, surprise), run_finished.
Pair tool_started / tool_finished by call_id.
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