dsh-file-memory
Native layered memory for DeepSeek Harness with persona files, workspace scope, semantic recall, and background consolidation
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Native layered memory for DeepSeek Harness with persona files, workspace scope, semantic recall, and background consolidation
Import Claude Code memory (CLAUDE.md) and conversation history into DeepSeek Harness as resumable sessions; /init scaffolds an AGENTS.md project memory file.
DSH 插件:/gamemode 1 = 一键切换到内置创造模式(cordis)预设。DSH plugin: /gamemode 1 = switch to the built-in Creative Mode (cordis) agent preset.
LMA (Layered Memory Architecture) 是一个为 DeepSeek Harness 设计的地基插件(Foundation Plugin)。它定义了 “记忆体(Memory Body)” 这一抽象概念及其挂载/卸载协议。 它与其他记忆插件的本质区别在于:LMA 是一个容器和载体,让 dsh-memory-evolve、EchoCore 等“能力性插件”可以挂载其上,它本身也内置了一套可开关的基础记忆流程,作为可选能力。LMA结束记忆功能的“一锅乱炖”,实现跨会话的结构化记忆机制。(目前功能还在持续完善以及测试,对于其他插件的接口在构想完整后逐步推动)
把 Codex(OpenAI Codex CLI / Desktop)的 MCP、技能、全局配置、记忆以适配 DSH 的形式迁移进 DeepSeek Harness(DSH 插件)
Project Memory gives coding agents a single, trustworthy memory for a software repository — so they stop re-learning the same facts and stop writing conflicting "memory" files.
Generic stateless dialogue compression that mimics human memory — forgetting-curve bounded context for LLM conversations, with a ready-to-use adapter module for DeepSeek Harness (DSH).
An original high-key prismatic memory theme for the DeepSeek Harness web UI.
本地优先的 Agent 五层记忆体组件 - DSH 插件
把 WorkBuddy 的文件式记忆系统移植进 DeepSeek Harness:用户级 + 工作区的人类可读 Markdown 记忆(~/.deepseek-harness/MEMORY.md 与 <cwd>/.deepseek-harness/memory/)。
dsh-df-memory
Cross-session long-term memory for DeepSeek Harness (dsh): durable JSON-file memory store with memory_save / memory_recall / memory_forget / memory_list model tools, installable as a dsh bundle.
Deploy the ArchGraph ARGO toolchain, skills, and rules (schema, scripts, argo-init skill, global rule) with one command.
大 engram 小 KV:外置 engram 转接层(跨会话分层记忆:global/project/session,AI 自主决策归属 + 因果链接索引 + 渐进披露 + 主动唤醒),为 DSH 实现超长上下文记忆稀疏路由,与官方 compact 共存(官方腾 KV,engram 保细节)
DSH bundle that bridges the Codebase Memory MCP code knowledge graph into DSH and can keep indexed repositories fresh with an optional debounced filesystem watcher.
Honcho memory for DeepSeek Harness — persistent, cross-session memory that survives context resets and restarts.
Conversation history recall for DeepSeek Harness: search the original text of every session (like searching chat records) — literal/fuzzy/semantic retrieval, fully local & offline. AI never forgets what you told it.
VSCode-like bottom status bar for DSH Web: conversation token usage, host CPU/memory with Linux-style colored char bars, clock, and a public API for other plugins.
Local, storage-bounded cross-session search for DeepSeek Harness conversations with SQLite FTS5, Chinese segmentation, and message-level jump targeting
给 DeepSeek Harness 补上时间轴记忆:定宽只追加的事实日志 + agent 自己维护的摘要金字塔,固定阅读预算下 recall 成本不随记忆量增长。
把「记忆」带进 DeepSeek Harness:极简文本记忆系统,双轨记忆(流水日志 + 人物/产品实体画像),大模型为核心驱动。无需安装其他软件,无需编译,无第三方依赖。
MemoryHub (mh) integration for DeepSeek Harness: loads .memoryhub checkpoint memory on session start, saves dsh sessions back into checkpoints, and registers the mh workflow skill and tools
Find and install DeepSeek Harness (DSH) plugins. Use when the user asks to add a capability to DeepSeek Harness, asks which DSH plugin does X, mentions dsh plugin add, or wants memory, vision, a terminal UI, themes, or any other extension for their DSH agent.
Native memory for DeepSeek Harness — auditable facts with evidence chains, powered by StateCore