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[Bug] Subagents executing long tool-call sequences in a single turn fail prompt caching and compound token consumption

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評估

難度
5/5
預估耗時
一週以上
新手友好度
35/100
Issue 類型
缺陷
描述清晰度
基本清楚
活躍度
活躍
技術堆疊
powershell, shell
領域
ai, cli, performance

研究方向

從 task tool 背後的子代理 harness 入口開始,檢查在漫長的 Turn 0 工具呼叫序列中 write_agent 訊息是如何排隊的。在 Windows 11/PowerShell 上重現 750-call 行為,然後驗證 harness 是否會讓出執行權或壓縮 context,以及 stop_agent 風格的取消是否能中斷正在執行的子代理。

由索引模型根據 Issue 內容生成。

描述

triage
Environment
  • GitHub Copilot CLI v1.0.83
  • OS: Windows 11 / PowerShell
  • Primary Model: Gemini 3.8 Flash
Problem Description

When executing autonomous subagents (such as custom agents via the task tool), the agent harness allows a subagent to run hundreds of tool calls within a single monolithic turn (Turn 0) without yielding or compacting context.

Because each tool execution (file edits, test outputs, build diagnostics) is appended sequentially to the conversation history of the active turn:

  1. Prompt Caching is defeated: The dynamic append of intermediate tool results changes the prompt prefix and prevents effective provider-side KV prompt caching.
  2. Exponential Token Compounding: Every subsequent tool call re-submits the entire growing history (75k-100k+ tokens) to the model. In our session, a single subagent ran ~750 tool calls in Turn 0, compounding to over 120 million tokens consumed in under 40 minutes on local test/edit loops.
  3. No Turn-Yielding / Throttling Mechanism: The agent does not yield control or checkpoint its context, and background interrupt signals (write_agent) are queued rather than preempting execution.
Expected Behavior
  • Subagent harnesses should enforce turn boundaries or context compaction/eviction after a reasonable threshold of consecutive tool calls (e.g. 15-20 tool calls) to preserve prompt caching and avoid runaway token compounding.
  • An explicit cancellation/stop API (stop_agent) should exist to immediately interrupt runaway background subagents.
Actual Behavior

The subagent executed 750+ tool calls in Turn 0 without yielding, burning >120M tokens on repeated compilation and test iterations, and could not be preemptively stopped via standard agent messaging.

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