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---
title: "Context Reset"
type: concept
tags:
- "agentic-ai"
- "context-window"
- "recovery"
sources:
- "Your-AI-Isn-t-Stupid---It-Just-Needs-a-Better-Harness--Lychee-Technology-Engineering-Blog"
last_updated: 2026-04-20
---
## Overview
Context Reset——当 [[Context-Anxiety]] 触发时Harness 将当前 Agent 状态保存至磁盘、终止实例、启动全新 Agent 的程序化操作,用于解决长周期任务超出单次 context window 的问题。
## Trigger Condition
```python
if (tokens_used / max_context) > 0.7: # 阈值需按模型调优
trigger_context_reset()
```
## Procedure
1. **Save state**: 完整项目状态写入持久存储(磁盘文件)
2. **Terminate**: 终止当前 LLM 实例
3. **Launch fresh**: 启动全新 Agent加载保存状态
4. **Orient**: 新 Agent 读取状态、定位自身、继续工作
## Why Not In-Place Summarization?
原地摘要summarize → keep in same context仍让模型在嘈杂、退化的上下文中操作。Context Reset 提供完全干净的上下文窗口——代价更高,但可靠性显著提升,适用于超长周期任务。
## Trade-off
- **In-place summarization**: 便宜,但 context 仍嘈杂
- **Context Reset**: 昂贵(需重新加载状态),但可靠性高
## Source
- [[Your-AI-Isn-t-Stupid---It-Just-Needs-a-Better-Harness--Lychee-Technology-Engineering-Blog]]
## See Also
- [[Context-Anxiety]] — 触发条件
- [[State-Externalization]] — 持久化状态文件格式
- [[7-Layer-Harness-Stack]] — 第 7 层 Constraints & Recovery 的核心机制