Digbench-Runs / README.md
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---
license: mit
pretty_name: Digbench Runs
---
# 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`.