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Auto Compact — DeepSeek Harness 插件(DSH Plugin)
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@ohmejj/dsh-auto-compact

Auto Compact

从设置中配置原生自动上下文压缩的 DeepSeek Harness 插件。

插件会安装到这里;不确定时保持 web。

npx -y @deepseek-ai/dsh plugin --profile web add @ohmejj/dsh-auto-compact@0.1.0
README兼容性版本

兼容性与来源证明

Auto Compact 以 @ohmejj/dsh-auto-compact 发布,当前版本为 0.1.0。Plugin Hub 会校验它的 manifest,并保存精确安装来源,便于复现安装结果。

DSH 兼容范围
*
运行环境
web
发布来源
npm
Registry 更新时间
2026/10/16

版本

0.1.0stable
2026/10/7

相关插件

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最新版
0.1.0
DSH
*
HMR
重启进程
Tree shaking
未声明可安全裁剪
解包体积
42.6 kB
文件数
17
Surface
web
许可证
MIT
发布源
npm
周下载
152
安全扫描
✓ v0.1.0 扫描通过
查看源码 ↗项目主页 ↗
README Badge

点击下方 Badge 复制 Markdown,粘贴到 README 即可。

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README

DSH Auto Compact

@ohmejj/dsh-auto-compact is a DeepSeek Harness bundle that configures DSH's native automatic context compaction.

It does not reimplement or duplicate the compaction provider. It configures the existing @deepseek-ai/dsh-compaction-basic provider in DSH's Agent preset: that provider measures the current context, preserves a recent tail, summarizes an older tool-balanced conversation range, and records the replacement as replayable DSH session events. This keeps the original event log intact and lets DSH recover from a provider-reported context-window overflow.

Install

dsh plugin --profile web add @ohmejj/dsh-auto-compact

Restart the selected DSH profile after installation. Open Settings → 自动上下文压缩 to edit the policy.

Default policy

SettingDefaultMeaning
Automatic compactionenabledChecks pressure before the next Agent step.
Trigger threshold80%Starts compacting at 80% of the routed model's context window.
Recent-context retention16%Keeps the latest 16% of the context verbatim.
Extra headroom65,536 tokensReserves room beyond the model output budget before pressure is evaluated.
Summary output cap8192 tokensMaximum generation budget for the summary call.
Ordinary / overflow retries1 / 1Additional attempts after pressure remains or the provider reports overflow.

Leave the summary provider and model blank to summarize using the current conversation model. Set both fields together to route summary calls to a dedicated model.

How it works

Agent pre-step / context overflow
  → native token meter measures the current session surface
  → native compaction provider selects an older tool-balanced region
  → an LLM creates a summary checkpoint
  → DSH replaces that region on the derived conversation surface
  → raw session events remain available for replay and diagnostics

The plugin persists its own resolved policy in the profile, mirrors that policy into the current Web Agent preset's nested compaction-basic row, then requests DSH profile reconciliation. New sessions created with that preset use the new policy; existing sessions retain the preset revision chosen when they were created.

Development

npm install
npm test

npm test builds the host and browser artifacts and runs the policy validation tests.