Plugins

Find photo candidates from the 2026 Qiandao Lake cycling race by bib number and visible gear, with local helper scripts and album snapshot comparison. Needs the event's photo album link; snapshot comparison uses Python 3.10+, bib OCR is macOS only (Swift and Apple Vision), and the optional gear ranking needs Pillow, PyTorch, Transformers and a local DINOv2 model directory.

UML sequence diagrams as editable .drawio files from a JSON spec: Python places participants, fragments and labels, the draw.io desktop CLI renders a PNG at 1x-4x, and Pillow verifies the output size. Generation is deterministic and refuses to overwrite a file edited by hand. Needs Python with Pillow 12.x and the draw.io desktop app; the default paths are Windows ones (Python under C:\Program Files\Python314, draw.io under D:\drawio) and can be changed in the settings card.

Offline A-share checkups as four agent tools: valuation percentile (PE/PB/PS history, with negative-PE exclusion for loss-makers and a sample-length floor) and financial-statement review (three-statement reconciliation, DuPont decomposition, red flags, peer percentiles). Bring your own data; the plugin never fetches quotes and ships no data source. Needs Python 3.8 or later (standard library only).

Read-only disk usage scan and interactive HTML cleanup report for Windows and macOS. Needs Python 3 on the machine; the bundled scan scripts run offline as child processes.

SMTP/IMAP email bridge with five tools: send, list, read, download attachments, and list folders. Needs Python; the send tool sends real email from your account, and the mailbox authorization code is kept in the profile's cordis.patch.yml.

Paste a Douyin video link (easy to copy from the Douyin PC app) and the plugin downloads the video, transcribes the speech offline into timed Chinese text, and imports it into Obsidian as a Markdown note. Built for DeepSeek Harness and for beginners building a personal knowledge base. Needs Python 3.10+ with playwright (it drives Edge), PyAV, sherpa-onnx and numpy installed, plus a SenseVoice model placed under %USERPROFILE%\.dsh\douyin-kb\models.

Visualizes Finesse 3 KatScript in the conversation and adds a drag-and-drop optical bench designer that generates the Finesse model. It scans every user and assistant message for KatScript or a Finesse Python cell and renders them in the background with the first Python interpreter that can import finesse (Finesse 3, NumPy and Matplotlib required; interpreter overridable with FINESSE_VIZ_PYTHON), keeping the code and figures under ~/.dsh/finesse-vis.

Socratic tutor tools for DSH: cited retrieval, page images, chapter index, session review, embedded console. Teaching behaviour lives in dsh-socratic-persona.

Requirement to a detailed design doc another AI can build from: the model fills a plan, the plugin validates it and emits a SPEC plus task cards, then independent review and implementation evidence check the result. Needs Python 3.11 or newer; the spec-graph engine it calls is bundled in the package.

Keep SSH, WSL and Docker projects in the native DSH sidebar. Group directories by environment while choosing full remote DSH or lightweight local Agent mode per project. Manage shared full-backend connections together, keep lightweight connections independent, and selectively sync local Skills with difference previews. Aimed at the Windows desktop client with Linux, WSL or Linux-container remotes that have Python 3 and Bash (macOS and Linux hosts untested); lightweight SSH needs an existing SSHFS mount, and Docker has not yet been run against a live daemon.

Bridges the official IAR C-SPY MCP server into DeepSeek Harness: build .ewp projects, start simulator or hardware debug sessions, and read variables, registers, memory, the call stack and target output from the conversation. Windows only, and it needs an IAR Embedded Workbench installation. Setup needs Python 3.10+, Git and network access to GitHub and PyPI.

AI-assisted research workbench with editable step workflows, on-demand skill binding, a live execution graph and in-project document review (needs a local Python with python-docx, python-pptx, openpyxl and PyMuPDF), while keeping existing projects on their original configurations. Requires DSH 0.2.2 or later.

Runs your kanban backlog during DeepSeek off-peak hours while the machine is idle: per-card git worktrees, evidence-gated completion, merge-back, and budget and idle gates. Linux or WSL only (needs bash, python3, git, jq, flock); initialise a git repo once with `npx dsh-offhours init`.

Windows-only, workspace-scoped Codex to DeepSeek Harness handoffs with durable replies, independent review and restart-safe endpoint discovery; no computer-use. Built on code vendored from ESROAMER/codex-dsh-collab and Dax233/dsh-codex-bridge; it mounts the same default /codex-bridge route as codex-dsh-collab, so do not install both with default settings. Needs Python 3.11+ and a one-time pairing command.

Writes a novel from one idea to a validated manuscript with a code-driven workflow: a JavaScript state machine runs the stages (constitution, outline, design, writing, validation, batch, export) and a 15-step per-chapter loop, PowerShell scripts validate each gate, and versioned checkpoints let a restart resume at the exact chapter. Nine subagent roles do the drafting and review. Needs PowerShell 7 (pwsh) and Python 3.7+; without pwsh the gates record a DEGRADED verdict and the run pauses.

Registers the video-studio skill in the DSH skill catalog. It builds a Chinese-narrated video from a script: edge-tts synthesizes the narration, the timeline is derived from each line's measured audio duration rather than estimated from text length, Pillow renders every frame deterministically and pipes the raw frames to ffmpeg as rawvideo, burned-in subtitles and SRT/ASS export come from that same timeline, physical-model sound effects and a generated score are mixed sample by sample with numpy, and QA runs in four layers: container, signal, temporal and page level (the page layer only when the browser engine is used). An optional Playwright-driven browser engine renders the whole film as Canvas2D instead, sending PNG frames through image2pipe. Needs network access for the narration, ffmpeg on PATH and Python with numpy, Pillow and edge-tts; the browser engine also needs Playwright with a local Edge/Chromium.

E-commerce order analysis skill for DSH: refund-type classification, return-rate statistics, interception and refund-abuse loss accounting, after-sales analysis with product warnings, delivered as a single Excel workbook with a per-order detail sheet and a sampling verification sheet (the agent builds it with Python: pandas, openpyxl, matplotlib).

Auto-detects whichever memory tool local Hermes uses, then reuses its skills and memory in DeepSeek Harness, with always-available recall. Needs python3 and a local Hermes installation; it only reads from Hermes.

Guide an agent through exporting selected OneLap cycling FIT files, validating data and coordinates, and uploading via a logged-in Strava browser session. Needs Python 3.9+ (standard library only) and an agent with browser and file-upload tools.

Converts formula-bearing Word documents into Markdown with LaTeX, handling OLE equation objects, native Word OMML equations and image-based formulas; keeps equation numbers and structure. Needs Python 3.9+ (or uv); OLE and image formulas are transcribed by a vision-capable model from rendered images, and rendering needs Windows or LibreOffice.

Converts Markdown into .docx with native Word equations (OMML), then exports a PDF to verify every formula renders. Needs Python 3.9+ with lxml, latex2mathml and python-docx; the PDF check also needs pymupdf and Word or LibreOffice.

Measures how much a short clip changed and when — changed-area share, displacement, cumulative drift — returning one labelled key-frame image plus the number behind each event; it does not pick shots for a storyboard. Needs Python 3.10+ with numpy and Pillow; reading mp4 also needs ffmpeg and ffprobe on PATH.

A configuration-only DSH bundle that connects the MCP server shipped with Scrapling to DeepSeek Harness over stdio, exposing its HTTP fetch and stealth-browser scraping tools for page extraction, browser actions, screenshots and network inspection. Requires Python 3.10+ with scrapling\[ai] (scrapling-mcp on PATH) and a Chromium-compatible browser (scrapling install).

Bilibili companion for DSH, derived from c1overzz/dsh-bili-scroll (do not install both: they share the plugin entry id bili-scroll). Understand any video with AI summaries, chapters and subtitles; make your own with edge-tts voice-over, captions and ffmpeg; publish, post dynamics, reply to fans and read creator stats (publishing and dynamics stay off until Creator mode is enabled); plus an optional daily curated feed report. First run needs a one-time in-app install of Python dependencies (a uv venv plus PyPI packages such as bili-agent and edge-tts) and a Bilibili QR login.