Long-horizon search agents accumulate large amounts of retrieved content across many tool calls, making context-budget efficiency increasingly important. A minimal intervention is to mask stale observations from the context as the trajectory progresses, but it remains unclear when this form of context management helps and why. We study observation masking through a systematic sweep over various agent backbones (4B to 284B parameters) and three retrievers on offline and live-web agentic search benchmarks. We find that the accuracy gain from masking follows an asymmetric inverted-U shape when plotted against the model's accuracy without context management: a plateau under weak retrievers, a peak when a strong retriever meets a mid-capacity model, and a sharp collapse when the model is saturated. This pattern reflects the interaction between retriever recall and the model's implicit filtering capacity, rather than either factor in isolation. Mechanistically, masking implements a token-for-turn trade-off: it removes observations the model has largely stopped attending to and pages the agent rarely re-opens. The added turns help when they convert failures into successes, but they fail when masking removes evidence the model would otherwise have used. We therefore reframe context management as a regime-dependent intervention and provide a holistic perspective for analyzing context use in agentic deep search. We release our scaffold and trajectories here (https://github.com/i-DeepSearch/observation-masking) to support future research.

翻译：长期搜索智能体在执行多次工具调用时会积累大量检索内容，这使得上下文预算效率愈发重要。一种最小干预措施是在轨迹推进过程中屏蔽上下文中的陈旧观察，但目前尚不明确这种上下文管理方式何时有效及其原因。我们通过系统扫描不同智能体主干网络（参数规模从4B到284B）和三种检索器，在离线及实时网页智能搜索基准上研究了观察屏蔽机制。研究发现：当以无上下文管理时的模型准确率为横轴时，屏蔽带来的准确率增益呈不对称倒U形曲线——弱检索器下呈现平台期，强检索器搭配中等容量模型时达到峰值，模型饱和时则急剧下降。这种模式反映了检索器召回率与模型隐式过滤能力的相互作用，而非两者独立作用的结果。从机制层面看，屏蔽实现了令牌与回合数的权衡：它移除了模型已基本停止关注的观察内容，并关闭了智能体极少重新打开的页面。当增加的回合数能将失败转化为成功时有所助益，但当屏蔽移除模型本可使用的证据时则适得其反。因此，我们将上下文管理重新定义为一种状态依赖型干预措施，并为分析智能深度搜索中的上下文使用提供了整体视角。我们在此处（https://github.com/i-DeepSearch/observation-masking）发布了相关支架与轨迹数据，以支持后续研究。