arc-agi-3-schema-traces

ARC-AGI-3 Schema Gameplay Trajectories This release contains 50 ARC-AGI-3 gameplay trajectories and a dependency-free scoring utility. The trajectories are split evenly across two collections: `gpt_5_6_sol/`: 25 GPT-5.6 Sol trajectories. `claude_fable_opus/`: 25 trajectories from Claude Opus 4.8 and Claude Fable 5. Each trajectory directory includes `run.json`, a streamed `events.jsonl` event log, sanitized session data, snapshots, and the shareable text/image files produced during the run. Layout `baseline_actions.csv` contains the human action baselines shared by both collections. Each `evaluation_results.csv` is a compact manifest of the corresponding 25 trajectories. Recompute all scores Python 3.10 or newer is recommended. The scorer uses only the Python standard library, so no packages need to be installed. From this directory, run: The command discovers all trajectory directories, streams all 50 `events.jsonl` files, reconstructs per-level action counts, recomputes every RHAE score, and prints one 50-row table followed by a summary table. By default it also verifies that the event-derived actions and scores match both `evaluation_results.csv` manifests. Useful options: The default command exits nonzero if a log is malformed, an action sequence is not contiguous, a baseline is missing, the collection does not contain exactly 25+25 trajectories, or a recomputed result differs from a manifest. Scoring For completed level `i`, with human baseline actions `h_i` and trajectory actions `a_i`, the per-level score is: Incomplete or missing levels receive zero. The raw game score is the weighted mean of the level scores, using the one-based level number as its weight. A completion cap prevents unfinished games from receiving more credit than the weighted share of levels they completed: The 115% per-level cap permits a more action-efficient trajectory to offset a less efficient level, while the final game score remains capped at 100%. In the terminal table, `Level actio