dsh plugin bundle porting the omp advisor subsystem: a per-session reviewer model that observes the primary transcript and injects severity-ranked advice (nit/concern/blocker).

DSH 官方公众号收录的 TUI 补位插件：Claude Code 风，鲸鱼顶栏/实时状态/流式思考/双击 Esc 回滚/上下文进度+TPS。npm 一键装。 DSH official WeChat featured TUI plugin — Claude Code style: whale bar, live status, streaming thoughts, double-Esc rollback, context bar + TPS. npm one-click.

DeepSeek Harness Desktop App: a local AI desktop workspace for DSH Sessions, projects, files, web research, plugins, and Office artifacts.

Three-tier memory control plane for DeepSeek Harness: persistent runtime context, searchable project documents, pluggable long-term memory, smart routing, supervised agent workflows, WebUI, and headless tools.

DSH 自动化插件：让 Coding 任务按计划在全新 Agent Session 中运行，并由用户或 Agent 创建和管理定时任务。 / Run coding tasks in fresh Agent sessions and manage schedules from DSH Web or an Agent.

DeepSeek Harness (dsh) 接入飞书/Lark bot，扫码即用：流式卡片、项目工作区、并行任务、多角色 Agent、跨会话通知、对话内模型/密钥管理与安全网守护（dsh 崩溃后飞书仍可自救）。A scan-to-connect bridge bot connecting DeepSeek Harness (dsh) into Feishu/Lark: streaming cards, workspaces, parallel tasks, multi-role agents, cross-session notify, in-chat model/key management, and a safety-net guardian.

A caring memory companion for DSH — three-layer auto memory, proactive calendar reminders, warm AI greetings, per-turn auto-consolidation, and inheritance of memories from other AI tools.

Unified notification push plugin for DeepSeek Harness (DSH): one minimal notify() API, 8 channel adapters (telegram/dingtalk/feishu/wxpusher/pushplus/serverchan/bark/webhook), dual trigger (auto session events + agent tool).

Noema long-term memory plugin for DSH: durable, inspectable agent memory with recall tools and a settings page.

DSH 会话管理插件：删除（回收站恢复/彻底清除）、统计、继续/暂停、打开日志目录、对话顶部抽屉、工作区分组与排序、上下文压缩阈值设置。DSH session manager: delete with trash/restore/purge, stats, continue/pause, log folder, header drawer, workspace grouping, context compaction threshold.

Visual conversation map for DeepSeek Harness — sessions as cards on a whiteboard: drag to arrange, double-click to chat, draw an edge to fork with injected context. ADHD-friendly spatial memory. · DSH 可视化对话地图

The ultimate 2-way bridge between OpenAI Codex and DSH: bidirectional chat sync, live Skills mount & auto MCP mirroring.

NPM-installable DSH Web plugin for managing archived sessions.

High-reliability Feishu/Lark bridge for DeepSeek Harness — QR one-click auth, multi-mode agents, card-based commands, zero-loss outbox, media in/out, session-log doctor, reusable DSH Web GUI

DSH(DeepSeek Harness)会话导航插件:按轮折叠的对话大纲面板,支持节点点击跳转、滚动位置高亮与轨迹视图同款配色。

Session-aware sandbox escalation compatibility plugin for DeepSeek Harness/DSH第三方模型会话沙箱升级兼容插件

DeepSeek Harness 个人中心:用量统计 / 自定义指令 / 成本估算 / 桌面宠物(纯本地，不联网）。 Personal center & custom instructions for DSH

Desktop cockpit for DeepSeek Harness (dsh): token usage & cost tracking, budget alerts, runtime auto-update with rollback, Quick Ask hotkey, scheduled tasks, session search. Win+macOS. DeepSeek Harness 桌面驾驶舱：成本/用量监控 · 自动更新 · 定时任务

本地优先、零普通运行时依赖的 DSH 项目记忆：有界会话冻结 Hot Memory、倒排 BM25 召回、生命周期与缓存命中优化、中英双语 GUI。 / Local-first DSH project memory with zero regular runtime dependencies: bounded session-frozen Hot Memory, inverted-index BM25 recall, lifecycle, cache-aware design, and a bilingual GUI.

DSH 上下文注入审计插件：统计 AGENTS.md 指令链/技能目录/工具 schema 的 token 成本，检测重复与冲突；Web UI 圆环面板 + context_audit 工具。Context Doctor for DeepSeek Harness: audit instruction-chain / skill catalog / tool schemas token cost.

Self-evolving memory for DeepSeek Harness (DSH): earned experiences, diary/fact semantic memory, concern tracking, and an append-only audit ledger.

Unified DSH checkpoints: session + workspace + config three-state snapshots with one-shot rollback — /checkpoint and /rewind commands, a checkpoint tool, automatic interval snapshots, a Settings page timeline with pairwise diffs, and seed-replay session r

DSH 自定义模型思考等级管理与偏好记忆插件：原生设计语言、全档位思考配置与无感隔离式跨会话偏好记忆。

DSH plugin: connect to MCP servers, discover tools, and register them for direct model invocation with retry logic and statistics