Zhongzhi1228/Recursive-Task-Synthesis-Trajectories

Recursive Task Synthesis Trajectories

This dataset contains 327,189 completed agent trajectories collected on recursively synthesized command-line tasks. Public identifiers are opaque and stable.

The trajectory JSON retains messages, actions, observations, and token counts. Token-level log-probability arrays and duplicated debug/session captures are excluded from the public packages.

• metadata/trajectories.parquet: searchable trajectory metadata.
• metadata/shard_manifest.jsonl: TAR sizes and SHA256 checksums.
• data/trajectories-*.tar: sanitized trajectory packages.

from datasets import load_dataset

trajectories = load_dataset(
    "Zhongzhi1228/Recursive-Task-Synthesis-Trajectories",
    split="train",
)

License, attribution, and modifications

This dataset is released under the Creative Commons Attribution 4.0 International License. See LICENSE for the complete legal text.

These trajectories were generated by agents interacting with tasks from the Recursive Task Synthesis dataset. The associated task lineage includes materials adapted from EuniAI/TerminalWorld, whose dataset card releases those materials under CC BY 4.0.

The task environments were substantially transformed through recursive synthesis and executable validation. The trajectory records were subsequently collected, filtered, sanitized, assigned public identifiers, and repackaged.

This license covers the original contributions and adaptations that the publisher has authority to license. It does not grant rights over third-party materials beyond what is permitted by their original terms. No endorsement by an upstream author or organization is implied.

If you use this dataset, please cite TerminalWorld:

@article{chu2026terminalworld,
  title   = {TerminalWorld: Benchmarking Agents on Real-World Terminal Tasks},
  author  = {Zhaoyang Chu and Jiarui Hu and Xingyu Jiang and Pengyu Zou and Han Li and Chao Peng and Peter O'Hearn and Earl T. Barr and Mark Harman and Federica Sarro and He Ye},
  journal = {arXiv preprint arXiv:2605.22535},
  year    = {2026}
}