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Preset；保留源会话，并可让目标会话暂停等待确认或立即继续。"},"metadata":{"category":"session","keywords":["fs-write","fs-read","env"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":164,"downloads":3707}},"versions":[{"version":"0.5.0","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"Totoro-qaq","repository":{"url":"https://github.com/Totoro-qaq/dsh-plugin-bridge"},"homepage":"https://awesome-dsh-plugin.com/p/Totoro-qaq/dsh-plugin-bridge/"},{"name":"@anionex/dsh-turn-rewind","title":{"en":"dsh-turn-rewind","zh":"dsh-turn-rewind"},"description":{"en":"Rewind conversation and workspace state, powered by a persistent Change Ledger.","zh":"对话回退：基于持久 Change Ledger 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Sessions: move, migrate presets, delete, favorite, review later, prioritize, tag, and annotate. 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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. Within a turn it supports skeletonized information compression with a low original-text retrieval rate; at the tail of a turn it supports a turn-tail intent summary implemented purely by content substitution; context content stays safe, and the whole process runs inside the official JSONL compression.","zh":"机制上与上下文压缩领域最响的两条公开路线同源：代码骨架闸门沿用 Headroom（Apache-2.0）的骨架化思路，其公开头条为「编程 agent 少 20% token、JSON 载荷少 60–95% token，答案不变」；估计器通道沿用 TokenPilot（arXiv:2606.17016）的缓存感知上下文管理思路，该论文报告长会话 agent 成本最高降低 60%。这两个数字都是来源方自己的口径，此处照引；本插件不自带 benchmark，不自称任何降幅。在此之上为 DeepSeek Harness 提供：在同一设置区选择压缩 Profile、调整 Auto Compact 触发水位并开关代码骨架压缩；基于 DeepSeek V4 官方 tokenizer 的精确计量与同修订计数校验；非支持模型自动 fail-open，保留原始工具结果。回合内支持骨架化信息压缩、低原文取回率；turn 尾部支持尾部意图摘要（turn-tail intent summary）且仅以内容替代方式实现；上下文内容安全，全程在官方 jsonl 压缩内。"},"metadata":{"category":"session","keywords":["shell","fs-write","fs-read","network","env","llm"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":7,"downloads":12337}},"versions":[{"version":"0.10.0","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"drscrewdriver","repository":{"url":"https://github.com/drscrewdriver/dsh-context-compression-improved"},"homepage":"https://awesome-dsh-plugin.com/p/drscrewdriver/dsh-context-compression-improved/"},{"name":"@vectorize-io/hindsight-coding-agents","title":{"en":"hindsight#coding-agents","zh":"hindsight#coding-agents"},"description":{"en":"Hindsight, agent memory that learns: long-term project memory with auto recall and retain, knowledge pages, deep reflection, and per-repo memory banks.","zh":"Hindsight：会学习的 Agent 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服务端的 recall/write 记忆工具。"},"metadata":{"category":"memory","keywords":["env"],"labels":["curated"],"sortKeys":{"tier":0,"stars":40816,"downloads":30658}},"versions":[{"version":"0.5.29","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"volcengine","repository":{"url":"https://github.com/volcengine/OpenViking/tree/main/examples/dsh-memory-plugin"},"homepage":"https://awesome-dsh-plugin.com/p/volcengine/OpenViking--examples-dsh-memory-plugin/"},{"name":"@agentscope-ai/reme-dsh-plugin","title":{"en":"ReMe#dsh","zh":"ReMe#dsh"},"description":{"en":"Connects DeepSeek Harness to ReMe's local-first, self-evolving personal knowledge base: automatically captures completed main-agent conversations as user-owned Markdown memory, searches conversations and source material through reme_search with BM25, optional embeddings, and wikilink expansion, and schedules daily memory consolidation.","zh":"将 DeepSeek Harness 接入 ReMe 本地优先、自进化的个人知识库：自动把已完成的主 Agent 对话沉淀为用户掌控的 Markdown 记忆，通过 reme_search 结合 BM25、可选向量检索和 wikilink 展开搜索对话与资料，并按日整理长期记忆。"},"metadata":{"category":"memory","keywords":[],"labels":["curated"],"sortKeys":{"tier":0,"stars":3688,"downloads":1949}},"versions":[{"version":"0.1.2","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"agentscope-ai","repository":{"url":"https://github.com/agentscope-ai/ReMe/tree/main/integrations/dsh"},"homepage":"https://awesome-dsh-plugin.com/p/agentscope-ai/ReMe--integrations-dsh/"},{"name":"@zilliz/memsearch-dsh","title":{"en":"memsearch#MemSearch","zh":"memsearch#MemSearch"},"description":{"en":"Shared Markdown memory for DSH and other coding agents, with automatic capture, pre-step context injection, searchable recall, and memory-to-skill self-evolution through a review panel.","zh":"供 DSH 与其他编程 Agent 共享的 Markdown 记忆，支持自动捕获、步骤前上下文注入、搜索召回，以及通过审阅面板实现 memory-to-skill 自进化。"},"metadata":{"category":"memory","keywords":["shell","fs-write","fs-read","network","env"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":2792,"downloads":2483}},"versions":[{"version":"0.1.7","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"zilliztech","repository":{"url":"https://github.com/zilliztech/memsearch/tree/main/plugins/dsh"},"homepage":"https://awesome-dsh-plugin.com/p/zilliztech/memsearch--plugins-dsh/"},{"name":"dsh-deja","title":{"en":"deja-vu#extensions/dsh","zh":"deja-vu#extensions/dsh"},"description":{"en":"Reads the session files forty-two other coding agents on this machine already wrote (Claude Code, Codex, Cursor, VS Code Copilot Chat, opencode, OpenClaw, Hermes, Kimi, Cline, Zed and more), including sessions from before it was installed: six tools (deja_recall, deja_session, deja_blame, deja_fix, deja_how, deja_remember), a /deja command, and optional automatic recall added to the runtime context. Local BM25 index, no LLM, no embeddings, no network (dsh plugin --profile web add dsh-deja).","zh":"读取本机上其他四十二个编程智能体已经写下的会话文件（Claude Code、Codex、Cursor、VS Code Copilot Chat、opencode、OpenClaw、Hermes、Kimi、Cline、Zed 等），包括安装之前的历史：提供 deja_recall、deja_session、deja_blame、deja_fix、deja_how、deja_remember 六个工具与 /deja 命令，并可选地把召回结果加入运行时上下文。本地 BM25 索引，不用大模型，不用向量嵌入，不联网（dsh plugin --profile web add dsh-deja）。"},"metadata":{"category":"memory","keywords":["shell","fs-read","env"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":1303,"downloads":4468}},"versions":[{"version":"0.23.1","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"vshulcz","repository":{"url":"https://github.com/vshulcz/deja-vu/tree/main/extensions/dsh"},"homepage":"https://awesome-dsh-plugin.com/p/vshulcz/deja-vu--extensions-dsh/"},{"name":"dsh-mnemon","title":{"en":"dsh-mnemon","zh":"dsh-mnemon"},"description":{"en":"Cross-agent, local-first persistent memory plugin for DeepSeek Harness (DSH), powered by Mnemon. It shares long-term memory across Mnemon-enabled agents and adds runtime memory, searchable project documents, semantic recall, knowledge graph, and a Sidebar UI.","zh":"由 Mnemon 驱动的 DeepSeek Harness（DSH）跨 Agent、本地优先的持久记忆插件。它可在支持 Mnemon 的 Agent 之间共享长期记忆，并提供运行时记忆、可检索项目档案、语义召回、知识图谱和 Sidebar UI。"},"metadata":{"category":"memory","keywords":["shell","dynamic-code","fs-write","fs-read","network","credentials","env","subagent","host-runtime"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":710,"downloads":46705}},"versions":[{"version":"0.5.35","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"omdsh-dev","repository":{"url":"https://github.com/omdsh-dev/dsh-mnemon"},"homepage":"https://awesome-dsh-plugin.com/p/omdsh-dev/dsh-mnemon/"},{"name":"misakanet","title":{"en":"MisakaNet","zh":"MisakaNet"},"description":{"en":"Failure-recovery memory: search and record failure-recovery lessons from real engineering sessions, with BM25 + semantic RAG retrieval and a lessons knowledge base.","zh":"失败恢复记忆库：从真实工程会话中搜索和记录失败恢复教训，支持 BM25 + 语义 RAG 检索和知识库管理。"},"metadata":{"category":"memory","keywords":["fs-read","network"],"labels":["curated"],"sortKeys":{"tier":0,"stars":543,"downloads":6150}},"versions":[{"version":"2.50.1","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"Ikalus1988","repository":{"url":"https://github.com/Ikalus1988/MisakaNet"},"homepage":"https://awesome-dsh-plugin.com/p/Ikalus1988/MisakaNet/"},{"name":"meow-memory","title":{"en":"dsh-meow-memory","zh":"dsh-meow-memory"},"description":{"en":"Project-scoped cross-session memory: seven-layer SQLite store (soul/user/project/fact/lesson/rules/topic) on node:sqlite, cache-friendly first-message injection plus per-message keyword hits, memory_remember/search/find_similar/read/update/project tools, and idle-window consolidation (\"dream\") with peak-hour suppression. Prompt texts ship as per-language data files — the framework supports multilingual users.","zh":"项目级跨会话记忆：node:sqlite 七层存储（soul/user/project/fact/lesson/rules/topic），首条消息缓存友好注入 + 每条消息关键词命中，memory_remember/search/find_similar/read/update/project 工具，空闲窗口自动整理记忆（dream，峰时抑制）。prompt 文案按语言数据文件加载——框架支持多语言用户。"},"metadata":{"category":"memory","keywords":["fs-write","fs-read","env"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":288,"downloads":9456}},"versions":[{"version":"0.32.0","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"Phant0Meow","repository":{"url":"https://github.com/Phant0Meow/dsh-meow-memory"},"homepage":"https://awesome-dsh-plugin.com/p/Phant0Meow/dsh-meow-memory/"},{"name":"@eduwork/dsh-memory","title":{"en":"EduWork#dsh-memory","zh":"EduWork#dsh-memory"},"description":{"en":"Local semantic memory and prior-chat retrieval with source references, editable memories, retention, forget controls, undo, and JSON import/export.","zh":"本地语义记忆与过往对话检索，保留来源引用，支持编辑、保留、遗忘、撤销及 JSON 导入导出。"},"metadata":{"category":"memory","keywords":[],"labels":["curated"],"sortKeys":{"tier":0,"stars":239,"downloads":671}},"versions":[{"version":"0.2.0","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"ECNU","repository":{"url":"https://github.com/ECNU/EduWork/tree/main/packages/dsh-memory"},"homepage":"https://awesome-dsh-plugin.com/p/ECNU/EduWork--packages-dsh-memory/"},{"name":"dsh-engramory","title":{"en":"engramory#plugin","zh":"engramory#plugin"},"description":{"en":"Long-term memory for DeepSeek Harness kept as plain markdown, one fact per file, readable in any editor. The `MEMORY.md` index has a hard 200-line / 25 KB cap enforced by `ctx.tools.guard()`: a write that would grow an over-cap index is denied, while a rewrite that shrinks it always passes, so an oversized index can be compacted step by step. The plugin never writes memories on its own — what is kept is decided by you and the model. The same store is also used by Claude Code, Codex, Kiro and OpenClaw.","zh":"给 DeepSeek Harness 的长期记忆，以纯 markdown 保存：一条事实一个文件，任何编辑器都能打开。索引 `MEMORY.md` 有 200 行 / 25KB 的硬上限，由 `ctx.tools.guard()` 强制执行——让已超限的索引继续变大的写入会被拒绝，而缩小它的重写一律放行，于是过大的索引可以一步步压缩下来。插件不会自行写入记忆，记什么由你和模型决定。同一个记忆库也被 Claude Code、Codex、Kiro、OpenClaw 使用。"},"metadata":{"category":"memory","keywords":["fs-write","fs-read"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":195,"downloads":1375}},"versions":[{"version":"0.2.5","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"tinqiao-oss","repository":{"url":"https://github.com/tinqiao-oss/engramory/tree/master/adapters/dsh/plugin"},"homepage":"https://awesome-dsh-plugin.com/p/tinqiao-oss/engramory--adapters-dsh-plugin/"},{"name":"@modusensus/dsh-mneme","title":{"en":"mneme#dsh-mneme","zh":"mneme#dsh-mneme"},"description":{"en":"The memory that dreams — cross-session memory for DeepSeek Harness: recalls you and your projects across sessions, consolidates memories while idle (autoDream), freezes conflicting memories for your review, and keeps a replayable audit trail. Memory stays on your machine as SQLite with human-editable Markdown mirrors; four-way recall (keyword, vector, BM25, entity graph) and an interactive memory panel ship with it, plus 10 model tools, an MCP server, an external API and a CLI. Summarization and consolidation run on the host model you already configured; with a local embedder, semantic search runs fully offline.","zh":"会做梦的记忆 — DeepSeek Harness 跨会话记忆插件：跨会话记住你与项目，空闲时自动巩固记忆（autoDream），冲突记忆先冻结待你裁决，全程可回放审计。记忆落在本机：SQLite 存储配可人工编辑的 Markdown 镜像；附带四路召回（关键词、向量、BM25、实体图谱）与交互式记忆库面板，另有 10 个模型工具、MCP 服务端、外部 API 与 CLI。摘要与巩固走你已配置的宿主模型；把嵌入换成本地模型后，语义检索可完全离线运行。"},"metadata":{"category":"memory","keywords":["shell","fs-write","fs-read","network","env","host-runtime","llm"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":179,"downloads":8963}},"versions":[{"version":"0.9.4","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"slow-stack","repository":{"url":"https://github.com/slow-stack/mneme/tree/main/dsh-mneme"},"homepage":"https://awesome-dsh-plugin.com/p/slow-stack/mneme--dsh-mneme/"},{"name":"dsh-git-memory","title":{"en":"dsh-memory","zh":"dsh-memory"},"description":{"en":"Local Git-backed long-term memory for DeepSeek Harness with hybrid CJK/English retrieval, cited context, transactional sync, previews, and rollback.","zh":"基于本地 Git 的 DeepSeek Harness 长期记忆，提供中英文混合检索、带引用的上下文、事务式同步、预览与回滚。"},"metadata":{"category":"memory","keywords":["shell","fs-write","fs-read","env"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":169,"downloads":907}},"versions":[{"version":"0.8.1","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"seriousz158","repository":{"url":"https://github.com/seriousz158/dsh-memory"},"homepage":"https://awesome-dsh-plugin.com/p/seriousz158/dsh-memory/"},{"name":"@a9i5k4/dsh-auto-memory","title":{"en":"dsh-auto-memory","zh":"dsh-auto-memory"},"description":{"en":"Proactive associative memory for DSH: zero-prompt recall injected at a fixed boundary, three-layer auto-consolidation, skill crystallization, and Astra-style context management - handoff ledgers and a PLAN whiteboard that survive context-window switches, water-level sensing with an auto-detected model window. Local Markdown storage, model-agnostic, zero deps; lexical 0GB floor with optional semantic tiers.","zh":"主动联想记忆 + Astra 式上下文管理：自动唤回（固定边界注入，前缀缓存友好）/自动沉淀/技能固化/交接账本与 PLAN 白板跨窗口续命/水位感知（窗口自动适配当前模型）。本地 Markdown 存储，模型无关，零依赖；词法 0GB 兜底，可选语义档。"},"metadata":{"category":"memory","keywords":["shell","fs-write","fs-read","network","env","subagent"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":151,"downloads":12733}},"versions":[{"version":"3.3.17","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"Aik358","repository":{"url":"https://github.com/Aik358/dsh-auto-memory"},"homepage":"https://awesome-dsh-plugin.com/p/Aik358/dsh-auto-memory/"},{"name":"dsh-memento","title":{"en":"dsh-memento","zh":"dsh-memento"},"description":{"en":"Bounded, layered, approval-gated, auditable cross-session memory: a typed `ctx.memory` seam with a zero-dependency SQLite provider, a `memory` tool, and frozen snapshot injection, plus the dsh-memory-protocol v1 rehearsal with an adapter registry and a distributable conformance suite.","zh":"有界、分层、带审批门、可审计的跨会话记忆：`ctx.memory` 服务 + 零依赖 SQLite 存储 + `memory` 工具与冻结快照注入，并预演 dsh-memory-protocol v1——适配器注册表与可分发的一致性套件。"},"metadata":{"category":"memory","keywords":["fs-write","fs-read","env"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":141,"downloads":5090}},"versions":[{"version":"0.5.28","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"PerryLink","repository":{"url":"https://github.com/PerryLink/dsh-memento"},"homepage":"https://awesome-dsh-plugin.com/p/PerryLink/dsh-memento/"},{"name":"@zseven-w/dsh-noema","title":{"en":"dsh-noema","zh":"dsh-noema"},"description":{"en":"Long-term memory for DSH agents — durable, inspectable memories with recall, search, browse and knowledge-graph tools, import from ten other AI coding tools, and a settings page.","zh":"为 DSH Agent 提供长期记忆——可检索、可检视的持久记忆，带回忆、搜索、浏览与知识图谱工具，支持从十个其他 AI 编码工具导入记忆，并附设置页。"},"metadata":{"category":"memory","keywords":["shell","fs-write","fs-read","network","env"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":131,"downloads":1663}},"versions":[{"version":"0.1.0-rc.6","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"ZSeven-W","repository":{"url":"https://github.com/ZSeven-W/dsh-noema"},"homepage":"https://awesome-dsh-plugin.com/p/ZSeven-W/dsh-noema/"},{"name":"stratagate-dsh","title":{"en":"StrataGate-AgentMemory","zh":"StrataGate-AgentMemory"},"description":{"en":"Recent conversations stay vivid. Older ones fade into summaries, not oblivion. StrataGate gives DeepSeek Harness six-layer, time-decaying memory, while lasting events and relationships settle into a knowledge graph. Bring your memories from other AIs with you—no need to start over.","zh":"近期对话保持清晰，久远记忆逐渐化为摘要，而不是消失。StrataGate 为 DeepSeek Harness 带来六层时间衰减记忆，并将长期事件与关系沉淀进知识图谱。还可以把其他 AI 中的已有记忆一起带过来，不必从头开始。"},"metadata":{"category":"memory","keywords":["shell","fs-write","fs-read","network","llm"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":127,"downloads":7611}},"versions":[{"version":"0.3.23","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"diqierjia","repository":{"url":"https://github.com/diqierjia/StrataGate-AgentMemory"},"homepage":"https://awesome-dsh-plugin.com/p/diqierjia/StrataGate-AgentMemory/"},{"name":"dsh-auto-memory","title":{"en":"dsh-auto-memory","zh":"dsh-auto-memory"},"description":{"en":"Claude Code-style auto-memory, natively: typed memory files (user/feedback/project/reference) with a MEMORY.md index auto-injected into the system prompt (zero footprint when empty); memory_write/read/list/delete follow Claude Code write rules (dedupe-and-update, absolute dates, cross-links); workspace-scoped and user-scoped layers, cross-process file locking with orphan-lock recovery, plain Markdown on disk, no external services, no embeddings.","zh":"原生实现 Claude Code 式自动记忆:类型化记忆文件(user/feedback/project/reference)+ 自动注入系统提示词的 MEMORY.md 索引,无记忆时零提示词占用;memory_write/read/list/delete 遵循 Claude Code 写入规则(查重更新、相对日期转绝对、交叉链接);项目级与用户级双层作用域,跨进程文件锁与孤儿锁自愈,记忆为磁盘纯 Markdown,无外部服务、无 embedding。"},"metadata":{"category":"memory","keywords":["fs-write","fs-read","network"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":108,"downloads":4881}},"versions":[{"version":"1.1.0","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"AskTheWay","repository":{"url":"https://github.com/AskTheWay/dsh-auto-memory"},"homepage":"https://awesome-dsh-plugin.com/p/AskTheWay/dsh-auto-memory/"},{"name":"memory-eternal","title":{"en":"memory-eternal","zh":"memory-eternal"},"description":{"en":"Self-built DSH memory plugin: SQLite persistent storage + database-level audit guard (enforceAudit) + audit log. Auto-captures knowledge after conversations, agents recall via memory_recall, supports Claude Code/Codex/Cursor multi-agent sharing. Zero external dependencies.","zh":"自研 DSH 记忆插件：SQLite 持久存储 + 数据库层审核守卫（enforceAudit）+ 审计日志。对话结束自动沉淀知识卡，Agent 经 memory_recall 按需召回，支持 Claude Code/Codex/Cursor 多智能体共享，零外部依赖。"},"metadata":{"category":"memory","keywords":["shell","dynamic-code","fs-write","fs-read","network","env"],"labels":["curated","needs-sandbox"],"sortKeys":{"tier":0,"stars":67,"downloads":11245}},"versions":[{"version":"0.17.0","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"EternalNight996","repository":{"url":"https://github.com/EternalNight996/memory-eternal"},"homepage":"https://awesome-dsh-plugin.com/p/EternalNight996/memory-eternal/"},{"name":"dsh-prime-memory","title":{"en":"dsh-prime-memory","zh":"dsh-prime-memory"},"description":{"en":"Layered memory for DSH whose agent-facing surface is 10 tools: high-privilege writes (memory_add, memory_delete, memory_import), rumination controls (memory_ruminate, _cancel, _status), and a memory graph (memory_search_graph, 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工具集（`mcp__cloudbase__*`），登录走 device-code 流程。"},"metadata":{"category":"tools","keywords":[],"labels":["curated"],"sortKeys":{"tier":0,"stars":1149,"downloads":2107}},"versions":[{"version":"0.2.3","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"TencentCloudBase","repository":{"url":"https://github.com/TencentCloudBase/CloudBase-AI-Toolkit/tree/main/dsh-plugin"},"homepage":"https://awesome-dsh-plugin.com/p/TencentCloudBase/CloudBase-AI-Toolkit--dsh-plugin/"},{"name":"@anysearch/anysearch-dsh","title":{"en":"anysearch-dsh","zh":"anysearch-dsh"},"description":{"en":"AnySearch-powered real-time web and vertical search provider for DeepSeek Harness.","zh":"基于 AnySearch 的实时网页与垂直搜索插件，为 DeepSeek Harness 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X、LinkedIn、Instagram、Facebook、Threads、TikTok、YouTube、Reddit、Bluesky、Mastodon、Discord、Slack、Telegram 等平台排期、存草稿或发布帖子；附带 postiz 工作流技能。"},"metadata":{"category":"tools","keywords":["env"],"labels":["curated"],"sortKeys":{"tier":0,"stars":547,"downloads":863}},"versions":[{"version":"0.1.0","publishTimestamp":1793066119,"source":{"type":"npm"},"engines":{"dsh":">=0.1.0"}}],"author":"gitroomhq","repository":{"url":"https://github.com/gitroomhq/postiz-agent/tree/main/plugins/dsh-postiz"},"homepage":"https://awesome-dsh-plugin.com/p/gitroomhq/postiz-agent--plugins-dsh-postiz/"},{"name":"@ethanyoq/dsh-invoice-downloader","title":{"en":"Invoice-Downloader#dsh-invoice-downloader","zh":"Invoice-Downloader#dsh-invoice-downloader"},"description":{"en":"Local IMAP invoice download, OCR, archive, and Excel reimbursement summaries for DeepSeek Harness.","zh":"面向 DeepSeek Harness 的本地 IMAP 发票下载、OCR 识别、归档与 Excel 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