Datasets:

guanning
/

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. path points into this dataset; source is 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.gz holds the run's own git repository (one commit per turn, tags start and cleared_level_<k>). Restore it with cd ewm/<reasoning>/P-<n> && tar xzf git.tar.gz; the working tree then matches the files in this directory (events.jsonl carries the final run_finished line 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.