Plugins

Five palettes for DeepSeek Harness — mono, warm sand, indigo, moss and a custom three-colour palette — each rebuilt in OKLCH for light and dark, with text and surface contrast solved per palette. Includes config export/import codes and a high-contrast mode.

Arknights PRTS Originium Protocol theme featuring interactive 3D crystal, tactical HUD, memory fragments, and boot sequence.

Four palettes for the DeepSeek Harness web UI — solid, glass, volume and neon — each with light and dark halves. Neon adds a scene light field with a 46px circuit grid, a laser scan that sweeps the conversation column only while a turn is running, HUD-style workspace labels in the sidebar, embedded MiSans Latin chrome type, and a 125% sidebar type scale that stays fixed while the conversation area zooms.

Adds separate Chat and Work modes to DeepSeek Harness, embeds DeepSeek's official chat page, and provides an animated desktop companion with quick chat and task-completion notifications.

A governed registry for MCP connectors (stdio and streamable-http): four-level fail-closed authorization, mcpServers JSON import that rejects malformed args, credential redaction at every output boundary, an agent bridge that returns an honest review verdict instead of a fake approval, and a /mcp-reg operator console plus a settings page.

Builds a Markdown knowledge base from your course materials, then drills you until every knowledge point reaches your target accuracy; each answer must include your reasoning.

A daily journal the agent keeps: the journal_record tool appends dated todos and memories, with optional detail and tags, to one JSON file per day under the DSH home; the right sidebar draws those files as a month calendar marked per day by open todos, finished todos or memories, with checkable todos and the selected day's entries below; and the duty sentence it adds to the system prompt is editable from the calendar itself.

Reads each third-party endpoint's own model listing and keeps llm-pi-ai's per-model reasoningEfforts in sync, so the composer offers the thinking levels a model actually has.

Model picker dialog with routing groups: a model that keeps failing hands the turn to the next usable model in its group, and the dialog also carries a metrics dashboard and a free-channel tab. That tab installs six channel plugins — Our Free Model (the only one that needs no login or API key), CodeArts, WorkBuddy, Trae, Qoder and Providers Hub — whose providers cover 23 platforms: Huawei Cloud CodeArts, Tencent CodeBuddy, WorkBuddy, Youdao LobsterAI, Qoder, TRAE, Cline, iFlytek Loomy, SenseTime Raccoon, MiniMax, Zhipu ZCode, Gemini Code Assist, Alibaba Accio, iFlytek AStudio, OpenCode, OfficeAce, AutoClaw, ModelScope, Qiniu, Codely, MonkeyCode, Baizhi Cloud and MagiCrew.

iOS 26 liquid-glass skin: one white-grey-blue fog field behind the whole window, a single 40px frost on top of it, a floating glass sidebar and reply bubbles. Light and dark palettes, no photo wallpaper, no dependencies (33 KB).

Registers an apiCost session projection that estimates DeepSeek spend from reported token usage at published peak / off-peak rates, in CNY and USD, over self, delegation-tree or verified-team scopes: a composer-dock pill and its detail panel, the /cost command, a session_cost tool, and GET routes for the view and the current rate card. A panel switch parks model requests at the llm/stream waterfall while peak rates apply and dispatches them unchanged once the off-peak window opens, so the call is billed at the off-peak rate with no failure reported to the session.

Todo sidecar for DeepSeek Harness: turn selected text into a todo, capture todos from a conversation, review them in a left sidebar panel, get due reminders as an in-app popup or an IM bot message, and export everything to HTML, Markdown, Excel, CSV or JSON.

Claude Code-style workbench in DSH: workspace/session sidebar, streaming document-style transcript with unified tool cards and thinking, Markdown and Mermaid rendering, dark theme, and a draggable overlay panel backed by an in-host HTTP/WebSocket service.

Share an existing OpenClaw Markdown workspace with DeepSeek Harness as bounded persona and memory context, with Sidebar browsing and editing.

Binds a Feishu/Lark bot to DeepSeek Harness over a WebSocket long connection: incoming messages run through an agent session and stream back to the chat, chat commands such as /attach manage the live session, and feishu_* tools let the model push messages.

One hub over every coding IDE you run — dsh, Claude Code, Codex, ZCode, Qoder, CatPaw, Trae, OpenCode. Zero-API: it reads each tool's own on-disk state and gives a session inventory, per-IDE usage with cache-hit rates, one-line resume commands, and a single .hub/ rule body wired into all eight via marker-delimited pointer files. The domestic-IDE adapters (Trae/Qoder/CatPaw) were verified against the installed binaries — a gap no overseas tool covers.

Project-level memory built around a ledger whose structure the AI designs per project; the plugin only handles detection, injection, write-back, archiving and git. Memories are split by meaning: the active ledger holds current state, the turn journal is append-only, and decisions, the goal tree and lessons are one-card-per-file (with a multi-dimension index over the card folders); the fundamental principles file can be changed only by the user. There is a single compaction mode: before compacting, the AI sorts the work into three buckets - what must stay in context and is re-injected verbatim, what is written to the project's _stash/ for later lookup, and what is dropped. When a conversation is opened in a container workspace holding several projects, it can be locked to one sub-project (the lock lives in the plugin's own home and survives restarts; it leaves no marker in your project). Also an activity log with five levels, where L4 stores the user's own words verbatim (never injected, queryable on demand). Before each compaction a verbatim capsule (user quotes, raw errors, changed files) is written to disk, and both the capsule and its source material survive a restart; a handoff document lets a new conversation resume the previous one. 21 tools, 12 subcommands, 39 settings (one of them switches whether the settings panel or each project's manifest wins). Runs locally, no runtime dependencies.

Browser provider for DeepSeek Harness: hand it a web task — open a page, click, type, fill a form, read what is on it — and it drives a real browser step by step, seeing an indexed table of what can be done on the current page instead of raw HTML or screenshots. Each step is one bundled-Jev decision rather than a full model turn (1.1 s median per step versus 2.8–3.6 s for chat-model turns in the repo benchmark), and the main conversation receives only the conclusion, so its context does not grow with the page. Targets come from the page it just read and a changed page is re-read rather than clicked blind, and it runs in the browser that Session owns, leaving your everyday Chrome untouched unless you switch to attach mode.

A research library panel and skill set for DSH: project folders, figures with registered provenance, drafts, references, data tables, journal profiles and submissions, plus writing, citation and Origin-plotting discipline for research agents.

OpenAI-compatible image generation for DeepSeek Harness — text-to-image, image editing and batch generation, rendered straight in the conversation.

星穹召唤 · DeepSeek Harness (dsh) 插件：二次元抽卡 + 和抽到的角色聊天 | A dsh plugin: anime gacha cards you can chat with

DSH 插件市场：浏览官方与社区插件，装之前先给出兼容性结论，一键交给官方安装管线。Plugin market for DeepSeek Harness: browse official and community DSH plugins with a compatibility verdict, and install them through the official plugin manager.

AI-agent-driven automated testing platform for DeepSeek Harness (dsh): drives the harness agent through long-lived multi-round sessions to write and run Markdown test cases, file bug reports, fix the code and re-verify the fix, with a per-project serial queue, a development board and built-in load testing.

Save whole turns — the question plus the full answer — as plain Markdown inside the session workspace, promote the good ones into a cross-project personal knowledge base, and let the model search it on demand. No database and no runtime dependencies.