neufagents/dsh-healthcheck

A context-compression plugin for small context windows (a 100K context is enough), token savings (5x fewer tokens), and month-long single sessions (billions of tokens).上下文压缩插件，兼顾小窗口(100k上下文足矣)省token(省5倍token)和超长会话(数月级别几十亿token单会话)。billion-context is all you need

DSH 插件：便捷无感的同窗口内对话回退，从不新建分支；自带轻量工作区备份，可一并还原文件（Claude Code /rewind 语义）。 · DSH plugin: effortless in-window conversation rewind — never forking a new session; ships a lightweight workspace backup that restores files together with the rewind (Claude Code /rewind semantics).

Import conversation history from 25+ AI coding agents into DeepSeek Harness as resumable sessions — tool calls, reasoning and results kept intact, with reverse export and sync. | 把 25+ AI 编程 Agent 的聊天记录导入 DeepSeek Harness 继续对话，保留工具调用、推理与结果，支持反向导出与同步。

DSH session manager: delete with trash/restore/purge, restore archived sessions, recent-activity stats, continue/pause, open log folder, unread markers, fork into a new chat, workspace grouping and sorting, context compaction threshold.

DeepSeek Harness session manager: delete, archive, move sessions across workspaces, migrate presets, favorites, review-later, search, filter, sort, prioritize, add tags & notes, and batch-manage sessions. | DSH 会话管理：删除、归档、跨工作区移动、预设迁移、收藏、待回看、搜索、筛选、排序、优先级、标签、备注及批量操作。

Same-origin in mechanism with the two loudest lines in context compression. The code-skeleton gate follows the skeletonization approach of Headroom (Apache-2.0), whose published headline is 20% fewer tokens for coding agents and 60–95% fewer tokens for JSON, same answers. The estimator channel follows TokenPilot (arXiv:2606.17016), which reports up to 60% lower cost for long-session agents. Both figures are theirs, quoted as-is; this plugin ships no benchmark of its own and claims no reduction of its own. What it adds for DeepSeek Harness: choose a compression profile, set the Auto Compact trigger level and toggle code-skeleton compression from one settings section, with exact DeepSeek V4 tokenizer measurement, same-revision count verification, and fail-open behaviour that keeps the original tool results on unsupported models.