Unverified50% confidenceFactExact time
Agent 的每一轮循环都需将完整历史上下文传入 LLM，导致 token 消耗随任务复杂度呈线性乃至指数增长
1
Sources
50%
Confidence
Long-term
Relevance
7/16/2026
First Seen
Sources
Related Claims
UnverifiedWhen an agent is in a loop, each call carries the accumulated conversation history, causing token consumption to grow linearly or even super-linearly with the number of iterations.77% similarUnverified在Agent应用中，每一轮推理-行动-观察循环都需要将完整历史上下文重新输入模型，导致Token消耗随任务复杂度呈非线性增长75% similarUnverified在智能体工作流中，历史交互作为输入Token累积，导致总Token消耗随任务轮次呈近似平方级增长73% similarUnverifiedClaude Code的代理架构意味着每次任务执行可能触发多轮模型调用，Token消耗呈指数级增长而非线性增长72% similarUnverifiedA typical ReAct-paradigm Agent may need to go through 5–20 loops to complete a complex task, with each loop involving at least one LLM call.72% similar
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