Plugin

Zhihu (知乎) for DeepSeek Harness: wraps the local pyzhihu-cli as 18 zhihu_* tools — 14 read-only (search, hot list, question, answer, user, feed, topic, notifications, collections) plus 4 publishing tools that are not registered until readOnly is turned off — with a web panel in the sidebar for login, config and lookups.

LiveBench leaderboard for DSH — discovers the release the official site currently publishes, then reads its CSV and category JSON, and renders model rankings in an isolated same-origin iframe opened from a button beside the composer. Search, organization / open-weight / reasoning filters, per-category sorting, task-level detail, up to four models side by side, CSV export; refreshes every 60 s by default (configurable 30–3600) and caches only to the plugin's own .cache/rankings.json.

Peer communication between conversations in one DeepSeek Harness process: list the conversations the workspace shows, link one under a nickname, message it without waiting for its turn to end, read its progress without waking it, and declare rules for your own tool calls.

Turns DSH permissions into 9 selectable presets (3 sandbox modes x 4 approval tiers), with rule plus LLM risk classification across four risk levels, password-gated approval for high-risk operations, and a JSONL audit log.

In-app local notification center for DSH: a sidebar Notifications entry with unread badge, full-screen center with level color coding (info/success/warn/error), time/source filters, sorting, title/content search, read/unread, delete, detail popup with one-click copy, and pagination; written by the notify_add agent tool or the dsh-localnotify CLI (with auto-cleanup retention), page refreshes live, UI follows dsh web language (zh/en).

Resume screening plugin for HR in DeepSeek Harness: ingest up to 100k Word/PDF/Excel resumes into one searchable library with skills / coarse categories / ingest time, auto-ingest & de-dupe new resumes, then screen by plain-language criteria — rule pre-filter in the database plus LLM fine-judge on the shortlisted few, CSV export. Works on DeepSeek Harness 0.1.7 through 0.2.x, tested on 0.2.0-rc.1.

Three-party collaboration protocol for dsh: Step List state machine, five-tier review chain (Gemini/web/Claude Code/dialog/manual), alternatives adjudication, cross-restart resume with heartbeat, and capability persistence.

DSH web plugin: a LiveBench tab in the Trajectory view (right of 对话/轨迹). Run LiveBench evaluations against every model configured in the DeepSeek Harness — pick provider/model, category, task, release and question range from dropdowns, watch progress, and

TOTP-only access control for personal DeepSeek Harness Web instances, with in-app QR enrollment, single-use recovery codes, live protection controls and lock-all revocation of page access.

DeepSeek Harness dashboard: per-session statistics (tokens, timing, tool and skill calls) as a dedicated Statistics view tab. Compatible with dsh v0.1.2-alpha.1 ~ rc.1 (see README).

Web management panel for Docker on DeepSeek Harness: manages Docker MCP servers (deploy/remove, official catalog search/pull, gateway start-stop-restart, custom deploy) and containers/images (list, start/stop/restart, remove, logs, inspect, interactive terminal, create, pull, build, load) across local CLI and SSH remote targets with one-click switching. Credentials are encrypted with Windows DPAPI, HTTP is loopback-only, and command parameters are whitelist-filtered. Build-free pure ESM; client is zero-dependency.

Unofficial host-side ServerChan alerts for DeepSeek Harness: sends a mobile reminder when an approval, plan review, or question stays unanswered past a configurable threshold, even with the browser closed.

Turn-end notification sound for DSH: built-in internet meme voices (ni gan ma ai yo, ji ni tai mei, shen ying ge, etc.), Settings panel with preview/switch/random, custom audio folder support.

Dual-endpoint Zhipu BigModel GLM provider catalog (Coding Plan and ordinary API) with live model discovery, live-tested thinking-tier mapping, and a settings card for keys, endpoints and the default reasoning tier.

Windows-only tray monitor for DeepSeek Harness: deploys and manages the standalone DshTaskWatcher tray app - four-state tray icon (gray=disconnected, green=idle, amber=running, red=attention), a per-task panel with live duration/tps/tokens, and completion & outcome notifications. Start/stop switch in Settings > Plugins; the watcher is an independent process that survives DSH restarts.

Smart calendar and checklist assistant with lunar dates, macOS/Windows native notifications, and WeCom push.

Auto-injects user-chosen skills into every DSH session, per prompt or once at session start, with a settings page, a composer indicator, and log-deduplicated session-start stamps; verified against DSH 0.1.3 source.

Prevents concurrent-write session corruption: takes a per-session advisory lock on session start and every step, so a second dsh process fails loudly instead of writing a duplicate-seq gap; dead owners are taken over automatically.

Collapses the composer to an iPhone-style home indicator while you scroll, then restores it on hover, click, or scroll up. Corner arcs dock the real composer into the left or right gutter.

Browser tab status indicator for dsh web: paints the document favicon from the session list (blue spinning while work runs, amber while waiting on the user, green when finished).

Plugin inventory manager for DeepSeek Harness Web: table view of installed plugins with status filters, enable/disable switches applied via HMR, config viewer/copy, uninstall and npm update reminders.

DeepSeek Harness 插件：语音 + 通知出口——agent 通过云端 TTS（火山 seed-tts / 小米 MiMo V2.5，失败自动回退 SAPI）/ 桌面通知 / 提示音主动联系用户。融合 dsh-plugin-notify 的 DSH 原生深度集成与 agent-voice-mcp-minus 的云端 TTS 调优，零 Python 依赖，Windows 原生。

Standalone mobile surface for dsh: scan-to-pair device trust, realtime SSE sync, three-channel completion notifications (in-app / Web Push / Server酱·Bark·Telegram), offline outbox, approval & question panels, per-provider usage meters, PWA; a native narrow-screen phone UI.

Auto-adjust model reasoning effort per task (off/low/high/max): task classification, \[effort=...] markers, in-turn error escalation, DeepSeek peak-pricing-period capping with countdown notices, and manual-selection priority.