Plugins

Local full-disk knowledge base: indexes documents from C:/ and E:/ into a SQLite FTS5 trigram index over filename, body, and path, with a searchable DSH sidebar panel, no-keyword browse, usefulness/topic tags, and a token-efficient kb agent tool. Windows only; building the index needs a system Python 3 with PyMuPDF and python-docx (plus python-pptx and openpyxl for PPTX/XLSX), and no prebuilt index ships with the plugin.

Three-tier memory (personal, project, session) built on the Hy-Memory engine, with relevant memories injected before each step. Ships seven memory tools (search, add, list, get, update, delete, forget), a settings panel with per-tier lists, editing, change history and duplicate cleanup, real token accounting per write, session summaries written by the engine at session end, and a user profile refreshed from recent memories. Memories can be exported to and imported from MemHub. Needs Python 3.11+ once to install the engine, or uv, which fetches 3.12 itself; uninstalling keeps the stored memories.

Floating A-share limit-up card in the DSH overlay showing limit-up, broken-board and limit-down counts, break rate, consecutive-board height, previous-day limit-up premium, top themes and a localStorage watchlist; closable with no floating remnant (restore from the sidebar footer). Needs the separate Python dashboard backend from the repo's dashboard/ folder (Python 3.9+, akshare; not shipped in the package), which the same-origin proxy can health-check and optionally autostart.

A local-first todo board for the DSH sidebar with Todo/Doing/Done columns organised by project, storing everything in one Markdown file inside a folder you pick on first run. Cards carry due dates down to the minute, a colour stripe, a private blur that hides the title until you reveal it, notes and per-project roles, and can be dragged between columns or onto another project. The agent also gets a kanban tool that reads and edits every card, masked ones included. On macOS it installs three launchd jobs that run /usr/bin/python3 and post system notifications (a 09:00 digest, a check every 30 minutes for cards due within 2 hours, a Monday weekly review), which you can retime or disable in the in-panel Automations tab.

Delegates coding tasks from DeepSeek Harness to Codex CLI in WSL, with required acceptance criteria, background progress and cancellation, thread resume, per-criterion reports, change tracking, and optional workspace guardrails. Requires Windows with WSL2, Python 3.11+ and a logged-in Codex CLI in WSL.

Serial-port toolkit for DSH - 9 tools plus a web UI where an AI agent and a human share one UART line, with auto port matching, hex/text frames, timestamps, scheduled sends, rule-based auto-recovery and appearance themes. The serial engine runs on Python 3.8+ — DSH's bundled interpreter is used when present, otherwise python / py -3 on PATH.

Intervals.icu-only endurance-coaching skill bundle that turns Intervals.icu training data (activities, intervals, streams, training load CTL/ATL/TSB/rampRate, HRV, resting heart rate, sleep in-bed hours, eFTP, power curves) into concrete training decisions: readiness gating, VDOT pace and heart-rate zones, periodized weekly plans written back to the Intervals.icu calendar as events after confirmation, session reviews, race-day pacing and fueling, and weather-adjusted workouts. The bundle registers the endurance-coach skill in the profile, ships deterministic helper scripts, reads an athlete profile created by its init script, and requires the agent to state when data is unavailable instead of inventing it. It needs a separately installed Intervals.icu MCP server for training data and Python 3.10+ for its bundled scripts; with neither it works only from numbers you type in.

Article Review page in DSH's native right sidebar: turns Markdown, Word, PowerPoint and PDF articles into sentence-addressable text, lets you comment on any sentence, and hands the open review to the agent as a composer draft. Six agent tools let the model read every comment, revise the article (in place for Markdown, as a sibling <name>.revised.md for binary formats), resolve the comments, and record recurring wording preferences into a long-term writing-style memory injected into later prompts. Extraction includes a dependency-free DOCX/PPTX reader; PDF text extraction runs locally through the host's Python + pypdf (or poppler's pdftotext) and is unavailable without one of them. No network calls, no telemetry.

odoo-lint for DeepSeek Harness: lint and fix Odoo addons, and lint every addon file the agent edits

Audits and evolves agent context at four scopes: a single repository, a group of related repos, a knowledge hub, or the whole machine. Discovers projects, instruction files, skills, tools, knowledge, state, evidence and credential references; reports drift, duplicate facts, broken pointers, budget overruns, unindexed knowledge, stale state and unregistered credentials; scores each scope on its own dimensions; and turns findings into reviewable migration plans that back up every file before moving it. The format contract is a versioned spec (CTX rules, markdownlint-style IDs) following open conventions — the AGENTS.md open format, llms.txt-shaped indexes, YAML front-matter note headers — now backed by published JSON Schema contracts (draft 2020-12) for the hub manifest and the plan JSON, plus an editor modeline that validates hub.yaml with zero configuration. The hub is declarative (schema 2, zones with light profiles, sections may live outside the hub root), a one-pass check command runs scan, doctor and score, and state writes are atomic and lock-protected; scoring stays honest about missing evidence — a waiver greens the gate, never the score. Ships a stdlib-only Python CLI plus two skills; credentials are referenced by path and never printed. Requires Python 3.9+ (stdlib only) and DSH 0.2.1-rc.2 or newer, below 0.3.0.

Blocks the end of a turn while temporary files from that turn are still lying around: it registers a listener on the serial agent/turn-stopping hook and, if anything is left, hands the model the file list plus two ways out — delete them, or justify each one and move it somewhere deliberate. Candidates come from two narrow temp-file sources, plus a backup-retention channel that is on by default and flags excess .bak copies of files touched this turn. The first is the .agent-tmp/ convention directory under the session cwd: whatever is left in it is reported outright, because that directory exists only for throwaway files. The second is the paths this turn actually wrote, captured through the fs/write-intent, fs/edit-intent and fs/delete-intent hooks; those are reported only when they sit under that cwd (compared after realpath normalisation), fall outside .git, node_modules, out, dist, build, target, vendor, .venv and the Python bytecode cache directory, match a temp-file pattern that requires a separator after the prefix so checkout.js and benchmark.ts are not taken for scratch files, and the file is still present — which keeps junk already sitting in the workspace from being resurrected as a complaint about this turn. One gate per turn, subagent sessions skipped, nothing deleted unless the backup mode is explicitly set to prune, and the injected wording follows the host locale instead of assuming a Chinese one.

Turns your local WeChat group chats into a followable todo board: a three-column kanban (todo / doing / needs you) with LLM summaries, automatic flagging of messages that @-mention or reply to you, drag-to-change status, and local-only storage. Needs a local Python 3 with sqlcipher3 and zstandard, plus the existing rion-wechat-reader config.json and keys.json for the WeChat databases; the plugin does not extract the keys itself, and summaries send the quoted chat text to the model you choose.

Adds an `ocsr` skill and an `ocsr_dispatch` tool that run headless `opencode run` as fresh-context, cross-vendor worker backends, with a Python driver for watchdog timeouts and per-worker output files. Windows only (Windows PowerShell): requires the OpenCode CLI, Python 3 and a model allowlist at `~/.ocsr/allowed-models.json`.

Unlock password-protected LabVIEW VI and CTL block diagrams without LabVIEW or Python.

arXiv paper survey assistant with a settings-page UI, a local knowledge base, a feedback loop, keyword search plus optional local-embedding semantic search, and per-paper deep-read notes. Requires a configured DSH LLM provider; semantic search and full-text deep read need an optional Python environment (pymupdf + fastembed), otherwise they fall back to keyword search or are skipped.

Self-hosted SearXNG search provider: the bundled installer sets up and supervises a local instance on macOS/Linux/WSL (needs git and Python 3.11+), key-less and tracking-free; it probes the engines your network can reach and applies the recommended set in one click.

Record lecture audio in a phone browser and transcribe it locally with faster-whisper; generates summaries, mind maps and quizzes with a wrong-question gate plus a focus report, and serves the phone UI over a built-in HTTPS tunnel from any network. Transcription needs local Python, ffmpeg and faster-whisper (the setup script installs them plus a ~460 MB Whisper small model); the public HTTPS tunnel uses a Windows cloudflared build and has no access code by default, so anyone with the link can open it.

Sidebar page that removes burned-in subtitles from a video with a local video-subtitle-remover checkout: frame preview with a start/end range, drag-drawn regions (up to six), automatic region detection reviewed by a DSH chat model, live before/after comparison, and open-file/open-folder on the result. Requires the video-subtitle-remover checkout with its models and a Python environment with torch, paddle and OpenCV.

A five-stage engineering loop for agent-built projects — spec, build, verify, ship, learn — with one artifact and one gate per phase, so an agent always knows the single next action. Role policy, project templates and deployment sit behind explicit ports: swap the implementation without rewriting the loop. Its scaffold generator lays out the internal layers of a project — `init --layout {none,webapp,service,plugin} --stack {python,node,none}` — from nine layers sampled out of three unrelated production projects: entry docs, an OpenSpec plan face, a spec truth layer (INDEX, one file per domain, TESTING, CONSTITUTION), a wiki split into knowledge / progress / runbook, the six `.agents/` slots, server+web, scripts/deploy/config, tests+e2e and a gitignored out/. Non-none layouts also gate the directory contract and compile every source root. Ships a Python CLI (init/next/check/ship/new) plus a local command adapter and an SSH/systemd adapter with release directories, an atomic current/previous switch, a deploy lock, a commit-versioned JSON probe and automatic rollback on a failed probe; bootstrap and teardown provision and remove the unit and the reverse-proxy block idempotently and refuse to delete a root they did not create. Includes a runnable example workspace and a skill that keeps the agent on one phase at a time. Requires Python 3.10+ and PyYAML; remote deploys need SSH access, rsync, systemd and Caddy on the target.

Control tower tools: dispatch a task to a role agent, read its report, verify and accept or send it back. Requires the separate agent-control-tower Python CLI (tower; it is not on PyPI — install it with pip install -e from the same repo) on the DSH process's PATH plus a tower init-ed workspace; without it every tool call fails with ENOENT.

Editable PowerPoint authoring workflow (a DSH-skill adaptation of icip-cas/PPTAgent) with concise Chinese business styling, HTML slide rendering and PPTX export review. Linux/WSL or macOS (Apple Silicon only); install LibreOffice, Chinese fonts, Node.js 22+ and uv first, then run the one-time setup, which creates a uv-managed Python 3.12 environment and installs Playwright Chromium.

Video study toolkit for DeepSeek Harness: fetch a public Bilibili single part or YouTube video, sample every 3 seconds plus change-triggered frames, transcribe locally with faster-whisper, page through section grids, and render a 16:9 study deck. Windows only, and needs the DSH pwsh tool plus Python 3.12 x64 with Pillow and FFmpeg/FFprobe; fetching adds yt-dlp, transcription needs faster-whisper with your own local model files, and deck output needs python-pptx.

Windows-only sidebar panel that watches the CPU and IO of your AI desktop apps' process trees and shuts the machine down once all of them have been idle for a configurable time, with a cancellable countdown, a dry-run mode and an activity log; requires Python 3.10+.

Local-first resume warehouse for DeepSeek Harness: package your work into reusable bullets, import an existing resume into a template, analyse a job description (including the school-tier preference it implies), assemble a tailored Chinese or English resume and export a PDF named position-name-school. The whole app ships inside the npm package — server/, web/, skills/, scripts/, requirements.txt, no git clone needed — and one tool starts, stops and health-checks it; the first start installs the dependencies into app/.venv. Needs Python 3.10+ and macOS or Linux (bash). Nothing leaves the machine except the LLM calls you confirm.