dsh-compaction

DeepSeek Harness Memory Low risk

Compaction backend replacing LLM summarization with a deterministic semantic extractor (keeps code/paths/commands, drops chatter) plus 28.4x KV-compression accounting.

压缩后端：用确定性语义提取器替换 LLM 摘要（保留代码/路径/命令，剔除闲聊），附带 28.4x KV 压缩记账。

How to install

DeepSeek Harness dsh plugin add github:ljsysfurryACE/dsh-compaction

About

dsh-compaction-agentframe AgentFrame 压缩后端插件 —— 把 DeepSeek Harness 的默认 LLM 摘要压缩替换为 **语义 + 物理双轨压缩**（28.4x KV 压缩思路）。为什么替换默认压缩默认 compaction-basic 用 LLM 摘要（有损总结旧对话），每次压缩都要一次 LLM 调用，且摘要可能丢细节。 AgentFrame 的思路： **语义轨**：MemoryDirector 判断哪些 token 值得保留（去闲聊、留关键） **物理轨**：吸收式 MLA + INT4 量化（270KB→7.6KB/token，28.4x） **效果**：保留关键信息 + 大幅省 token + 不额外调用 LLM 使用在 profile 的 cordis.patch.yml 中把 compaction-basic 替换为： yaml id: compaction-agentframe name: '@deepseek-ai/dsh-compaction-agentframe' config: semantic: true retainRatio: 0.2 physical: true 配置 | 字段 | 默认 | 说明 | |------|------|------| | semantic | true | 语义压缩（保…

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45 Tool quality · Based on stars, downloads, maintenance, security and docs

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Basic safety check

Findings: curated 收录但无 npm 包/安装命令
Sources: curated:awesome-dsh-plugin.com, curated:awesome-dsh-plugin/awesome-dsh-plugin
Topics: context-compression, deepseek-harness, dsh, llm, plugin

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