TerminalWorld: Benchmarking Agents on Real-World Terminal Tasks
We introduce TerminalWorld, a scalable data engine that automatically reverse-engineers high-fidelity evaluation tasks from "in-the-wild" terminal recordings. Processing 80,870 terminal recordings, the engine yields a full benchmark of 1,530 validated tasks, spanning 18 real-world categories, ranging from short everyday operations to workflows exceeding 50 steps, and covering 1,280 unique commands. From these, we curate a Verified subset of 200 representative, manually reviewed tasks. Comprehensive benchmarking on TerminalWorld-Verified across eight frontier models and six agents reveals that current systems still struggle with authentic terminal workflows, achieving a maximum pass rate o...
| Authors | Zhaoyang Chu, Jiarui Hu, Xingyu Jiang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 21 May 2026 |
| Last updated at source | 21 May 2026 |
Models and datasets referencing this paper
- EuniAI/TerminalWorldDataset
- andylizf/TerminalWorld-Seeds-CleanDataset
- andylizf/TerminalWorld-SeedsDataset
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