Plugins

Per-workspace skill visibility: each workspace binds one named switch table, so which skills the model may call on its own follows the project instead of every installed skill being listed every turn. Cannot be installed together with dsh-skill-scope.

Adds the MathWorks MATLAB Agentic Toolkit skills and the MATLAB MCP Server tools to DeepSeek Harness. Needs a local MATLAB R2021a or later. Installs from the plugin's own prebuilt release archive. A DSH restart is usually unnecessary: the market mounts the plugin live, and a page refresh shows the MATLAB settings page; restart only when the market reports that the live mount failed. By default (autoProvision) it downloads the MathWorks MCP Server binary and installs the newest Agentic Toolkit release on first use. With the China download region or a configured GitHub prefix, both are fetched through the fastest measured acceleration prefix first (the plugin's own, DSH's market setting, or the built-in gh-proxy.com and ghfast.top routes) and then directly. The downloaded server binary is verified against the SHA-256 digest GitHub publishes for its release asset when the release metadata can be read, and a mismatch refuses the install; if api.github.com cannot be reached the digest is read through the same mirror, so the check then only catches a corrupted or truncated download. MathWorks telemetry is disabled by default; set disableTelemetry to false to re-enable it.

Per-session control of which skills and MCP tools/servers the model can see (built-in tools are untouched): default shows everything, auto asks the model each turn what to keep, smart picks from your saved groups, or tick groups by hand, with a switcher under the composer and fail-open to full visibility on any error. The default state is auto, which adds one model call per turn (the session model unless judgeModel is set).

Registers a battle-tested development delivery rulebook as a skill family - one core skill (clarification, delivery checklist, navigation) plus nine focused skills (layered architecture, evidence-driven debugging, minimal changes, impact-graded verification, migration feature parity, async UI feedback, sizing rules, CLI safety and cleanup, project notes). Only the skills matching the current task are loaded, trivial tasks (small reversible single-file edits) are exempted outright, so each session pays tokens just for the rules it actually uses.

Context control for DeepSeek Harness: inspect token usage across request and conversation; switch skills, MCP servers and plugins between loaded, brief and hidden per session; toggle prompt sections and tools; compact on demand or at a configurable 5–95% threshold.

Hearts of Iron IV modding bundle for DeepSeek Harness: registers 15 skills covering focus trees, events, decisions, ideas, characters, technologies, localisation, GUI and error.log triage, and mounts 20 local MCP tools (a Python stdio server) to scaffold content, statically validate mods, build a SQLite FTS5 knowledge base from the vanilla game, and preview focus trees offline. Ships a 163-document reference library; requires DSH >=0.2.0 <0.3.0 and Python 3.9+ on PATH (standard library only, no game assets).

Manage Claude Code, Codex and Grok CLIs inside dsh and dispatch tasks to them as headless subagents, with dsh models, skills and tools bridged into each task, resumable CLI subsessions, and a hierarchical task board in the right sidebar (the board tab requires the separate DSH-better-sidebar plugin; without it the tab is not registered).

Knowledge-planet (zsxq) knowledge base skill: sync posts and attachments, extract docx/PDF text, guide topic category, summary and quote enrichment, rebuild the index, and search. Requires Python ≥3.10 with the packages in requirements.txt plus your own zsxq account cookie.

Skill manager panel for DeepSeek Harness: scans the six workspace and user-level skill roots, files every skill into fifteen built-in type cards (and any types you create yourself), and lets you move a skill between types without editing its files. A model you pick writes a one-sentence Simplified Chinese description for each skill, and can draw the icon for a custom type from the type name and the skills placed in it. Also reports which skills name each other in their bodies, and checks installed versions against SkillHub and upstream git sources.

Build presets for DSH Agents: package personas, prompts, skills, tools and runtime contexts into reusable capability bundles. Each task loads only the components it requires.

Meshy 3D generation and 3D printing skills driving meshy-cli through the shell: text-to-3D and image-to-3D, texturing, remeshing, rigging and animation, format conversion, and print-ready 3MF/STL with printability repair and slicer handoff. Bundles the CLI and keeps the sign-in on the host side, with a Meshy sidebar page, a Settings → Meshy page and an interactive GLB preview in Web and Desktop; installable as `meshy-dsh`. Needs a Meshy account; generation spends Meshy credits after you confirm the cost.

Registers one native DeepSeek Harness skill, design-taste-frontend — an MIT port of tasteskill v2 — for designing, redesigning and reviewing landing pages, marketing sites, portfolios, product pages and app screens (dashboards, admin, settings, inboxes). Directions are dealt by script instead of improvised: three of 20 researched art directions, then the chosen direction's hero composition, section blueprints, type system, palette, photography set and motion entry, drawn from a library of 58 hero compositions, 185 section blueprints, 44 type systems, 56 palettes, 19 photography sets and 18 motion entries, remembering recent draws so consecutive projects do not converge. The house style is measured, not asserted — a static lint plus a real-browser inspector at 1440/768/390 checking headline lines, type, colour, rules, shadows, gradients, contrast and overflow — and the agent then iterates on its own screenshots against a juror's rubric, up to three rounds. Openly licensed photos come with title, author and licence recorded for attribution. Node 22+; Chrome/Edge/Chromium only for the visual checks, and without one it falls back to the static lint and says so.

Skill catalog with independent model and user manual invocation controls for file-backed Skills, live source reads, read-only non-file Providers, and safe cleanup of missing policies.

Inventory of the MCP servers, skills and hooks a DSH profile has, plus a conversation tab reporting every tool, skill and MCP server a session actually called.

DSH design-delivery plugin with 10 tools for UI lint, design tokens, three-candidate shortlists, JND parameter probes, and PPTX deck check/export/render. Deck tools need ppt-master, Python with python-pptx and DSH's LibreOffice Kit; design_capture needs a real browser.

A settings-tab workshop plus the cordis-plugin-development skill it hands to the agent, for writing DSH plugins against the running host API.

Import Agent Skills from Git repositories, group them by repository, and enable or disable each one in DSH settings.

Context handoff sentinel for DeepSeek Harness: three behavioral recall tests (constraints / changed files / next step) run after every compaction or on /guard check, cross-checked against the session log, returning a green/yellow/red verdict plus an optional handoff document.

把 DeepSeek 養進 Instagram — a DSH plugin that gives an agent an IG life

DSH bundle of the 27 promoted skills from mattpocock/skills v1.3.2 (TDD, code review, grilling, spec and ticket flows, domain modelling), bodies byte-identical to upstream and upstream invocation policies preserved; ships a sync script and an offline contract check.

Group skills into named sets, toggle any combination, drag to reorder, and preview each group catalog token cost.

Diagrams a reader understands on first look: nine types from one JSON spec, with a checked title, reading path, legend, contrast and connectors. Requires Python 3.9+ for the render and check scripts.

Turn a script into a narrated explainer video: text-card slides by default (fast and exact for tutorials) or AI-generated footage per segment (needs AGNES_API_KEY); 14 online neural Chinese voices plus 3 offline Windows voices, with a one-command sample pack for picking a voice by ear. Requires ffmpeg, and the bundled video-remix skill copied to <workspace>/.dsh/skills/video-remix with npm install run there for the online voices.

Lingshu (灵枢) is a brain-inspired persistent memory, persona and growth system for AI coding agents: pure Python standard library, zero dependencies, local-first, requires Python 3.9+. Hippocampus/cortex layered memory with forgetting curves, dream consolidation, fuzzy associative recall, emotion system, persona drift protection, knowledge base, self-authored skills, and a local web panel. Ships as a DSH bundled skill; the separately installable cordis startup-injector plugin auto-injects sessions only when Lingshu is installed at ~/.dsh/skills/lingshu (or brainPy is configured) and Python 3 is available; the optional update check contacts GitHub/Gitee.