AI操作电脑：点鼠标不如写代码？
让AI帮你操作电脑，是让它像人一样点鼠标，还是直接写代码？这篇论文给出了反直觉的答案：在440个真实桌面任务上，纯鼠标操作的GUI智能体成功率59.1%，高于写代码的CLI智能体48.2%。但一旦给CLI智能体补上缺失的指令集，成功率立刻反超到69.3%。也就是说，CLI的短板不是模型能力，而是你还没教会它所有命令。这不是你明天就能用的工具，但它告诉你：未来AI操作电脑的瓶颈不在“会不会点”，而在“会不会写”——以及你愿不愿意给它写全指令。
📄 原文摘要(英文)
Computer-use agents can execute software tasks through either graphical interfaces or programmatic command interfaces, but existing evaluations confound interaction modality with differences in tasks, initial states, verifiers, and permitted actions. We introduce a matched execution-layer benchmark of 440 desktop tasks across 18 applications and 12 workflow categories, where screen-only GUI agents and skill-mediated CLI agents receive identical goals, states, and final-state verifiers while being restricted to modality-native actions. In this controlled setting, the strongest GUI agent reaches a 59.1% full pass rate, outperforming the strongest original-skill CLI agent at 48.2%; however, verifier-guided skill augmentation raises CLI success to 69.3%, showing that much of the CLI deficit comes from incomplete skill coverage rather than model capability alone. These results suggest that GUI and CLI expose different execution bottlenecks: GUI agents are limited by reliable grounded interaction over long-horizon workflows, whereas CLI agents are limited by the coverage and scalability of their skill interfaces.