Plugins

A fork of PC2005-cloud/dsh-pet adding Claude-themed whale-girl pets in standing and chin-rest poses, randomized activity chains, and laptop work transitions. Replaces the original plugin; do not install both together.

Kizuna agent letterbox: four tools that let an agent read its own inbox (mailbox status, pending letters, one letter in full) and answer a letter with completed / failed / input-required / working state. Kizuna is an agent directory with a reliable task relay: a per-agent kizuna-box on the same machine holds the inbox, retries unanswered deliveries after 3 / 10 / 30 / 60 / 120 minutes and records every delivery attempt in an append-only trail. The plugin talks to the local loopback box only and holds no credential.

Caps the lifetime of DSH desktop's dsh-auth-* session cookies at 7 days, so they stop piling up in the Cookie header until startup fails with HTTP 431.

MATLAB in the sidebar: a VS Code-like .m editor backed by a persistent MATLAB session (first boot ~6–9 s, then 12–84 ms per run in the default session mode, where figures really open on the desktop), live workspace variables you can edit, .mlx preview, extra folder mounts, and an agent-facing matlab_run tool. Requires a local MATLAB installation.

Wire up Feishu/Lark from a four-step wizard that discovers your chats instead of asking for a 32-character id, creates the app by scan, and runs a nine-item live self-test that names the exact scope to enable when a check fails. It drives a companion MCP server of 25 tools, including ones that move local files into a chat and pull a message's attachments back to disk. The MCP server is a separate install: take dsh-feishu-mcp-<version>.mjs from the dsh-feishu Releases (or npx github:yinsang0910-star/dsh-feishu-mcp); until it is in place the self-test reports MCP as not mounted and no mcp__feishu__* tool exists.

Bilibili live-room danmaku for DSH: read live chat, send messages only after explicit confirm, hang out in a room in the background, optionally let the model decide whether to reply, and optionally transcribe stream audio to text; no video understanding. Setup needs a Python 3 venv with the bundled requirements plus Bilibili cookies; transcription additionally needs ffmpeg and a Whisper engine.

Replies to DingTalk direct messages as your own account — reads the bound DSH workspace, writes the answer, and sends it back through the dws CLI.

Bottom-right DSH-styled Windows cards for approvals, questions, plan reviews and finished runs: click to jump back to the app that started the session (DSH by default), close with the × button, or let it close when you return.

Defines multi-agent team rosters as YAML or JSON files, validates them, bridges each member into dsh-agent-teams member arguments, and verifies the result against the running team.

RunningHub cloud ComfyUI workflows as a background task pool: submit a batch, and a watcher dispatches it within a concurrency budget, polls each job, downloads every output to disk, and wakes the session when the pool drains. A shared ledger records batches, costs, instance tiers, submit and finish times, and per-file save paths, with a live board in the right sidebar.

Bilibili curation floating panel for DSH: learns your interests on a probability schedule and decays them by half-life, picks videos inside a token budget derived from a daily money cap, and mentions you only when a fit score passes a threshold. Comments are off by default; once enabled they run in draft-and-confirm or self-checked auto mode under a daily quota, with a hard no-comment rule for political, government and frontier-science topics, and comment text is scrubbed for account identifiers before it can be posted. It signs in through your own Bilibili account cookies; a separate posting account is recommended.

Manage skill experts in the sidebar and summon them from the composer or @ menu.

Bundled Pixiv skill backed by a Python CLI: search illustrations, manga and novels, browse daily/weekly/monthly/rookie/original/AI/R-18 rankings, look up works, novel series and artists, and download originals, with multi-page works merged into PDF, ugoira converted to GIF and novel series merged into TXT; requires Python 3.9+ with requests, img2pdf and Pillow installed (pip install -r requirements.txt), and R-18 content needs your own Pixiv cookie.

Normalizes every generated .docx to one Chinese official-document layout: XiaoBiaoSong title, FangSong body at a fixed 29pt leading with zero paragraph spacing, character-unit 2-character first-line indent, fully centered table cells with repeating header rows, and a centered footer page number. Long attachment entries are split into real paragraphs at the wrap point measured by Word, producing a 2 / 6 / 5 / 6 character indent ladder. The plugin disables itself when the request mentions a lab report, and writes no signature block unless asked.

Let DSH speak: every reply is rewritten into natural spoken language before being read aloud, with code, tables, and Markdown handled gracefully. Works out of the box with system TTS; Doubao (third-party API) adds dialects and expressive voices; the local Kokoro engine runs offline to keep content on your device. Supports both DSH desktop and dsh web. Optional session sounds tell you when the agent is working, finished, or waiting for your answer — with swappable built-in tones and support for your own audio.

Qwen media tools: multimodal video and audio understanding, text-to-speech with preset voices, and scene audio generation, through Alibaba Cloud DashScope.

Big Fish Voice: makes the DSH web desktop pet speak. Whisper bubbles are read aloud automatically, left-clicking a bubble reads it, right-click/long-press reads it again, and clicking the pet replies with lines like 「主人，小鱼在这呢」. 10 offline Chinese voices: 2 local replica voices (鱼鱼酱 / 鱼鱼姐, no API key, ~58MB each) plus 8 Kokoro female voices (4 moe / 4 onee-san, models download on first use ~348MB, then work offline). Auto-reading can be throttled (unlimited / 30s / 60s / 3min); within one DSH instance only a single page plays audio. About 35KB package, inference in a worker thread, no dsh-pet files modified. The two replica voice models are for personal non-commercial use only.

Multi-engine image generation inside the conversation: an agent tool plus a composer-dock panel with an on/off switch, engine presets (Volcengine Ark, SiliconFlow, OpenAI-compatible, custom) and local spend tracking. You supply the API key for the engine you pick.

One MCP tool surface over two Windows desktop-automation backends (dsh-computer-use-win and windows-mcp). Both must be installed first: dsh-computer-use-win as a DSH plugin, windows-mcp via uv tool install windows-mcp --python 3.14, then run the bundled scripts/patch-backend.mjs once (it rewrites the local windows-mcp source; without it screenshot/read_webpage/launch_app fail) and disable the standalone wincu mount. It merges their 44 tools into 29 by dropping 10 duplicates, 4 dangerous ones (PowerShell, Registry, FileSystem, Process) and 1 tool-management entry, and blocks dangerous calls before forwarding through a reversibility-graded guard.

QQ Zone poster for DeepSeek Harness: scan a QQ login once, then let the model publish posts with mood-matched sticker images, with a daily cap and a silent headless Chrome session.

Chinese writing-register plugin for the Gcores/机核 editor 白广大: registers a 40 KB style skill plus style_lint / style_audit / style_rules tools — 4 hard-error and 27 warning checks (banned connectives, slogan inflation, empty quantifiers, uniform paragraphs, unsourced statistics, AI clichés), with thresholds calibrated on 444 articles / 802k characters; a settings page adds an on/off switch, single and batch trial runs, and JSON threshold overrides.

Local-first experience library for DeepSeek Harness: indexed markdown knowledge with error-signature retrieval, failure capture, gap-to-entry closure, and a sidebar panel. Ships a sanitized starter library. No network access.

Project-scoped SQLite memory with progressive retrieval, bounded context, a composer button and visual review. Install the repository-root DSH bundle, then run /learning-init with an absolute project path using local Python 3.10+.

Roleplay companion memory for DeepSeek Harness (short, human-like chat style by default): per-conversation editable persona documents with 1-100 weights per entry (AI may also refine them in small, story-driven steps), per-speaker favorability tracking (multi-person chats), AI self-evolution of traits and preferences, recent 48-hour transcript search, companion-style conversation compression that keeps long chats alive, and a date-archived local knowledge base with auto-packing by turns or tokens.