Plugins

Skill that reviews your coding-agent session transcripts (Claude Code and Codex only; DSH's own transcripts are not supported) over the last two weeks and reports which skills, hooks and rules work, need attention or go unused. Requires Python 3.

Engineering checklists distilled from Gillespie's Fundamentals of Vehicle Dynamics: 164 cards over the book's ten chapters, one skill entry with two-level routing. Each card gives the inputs a computation needs, the procedure, the boundary conditions where the method stops being valid, and a page reference — the explanation itself stays in the book. No passage of the book's prose is reproduced; 44 defects in the source (misprints, OCR damage, internal contradictions) are documented in the cards, each carrying a review-list ID. A study aid, not a substitute for the book.

Bundles the kb-curator skill, which keeps a local three-layer knowledge base and refuses to index anything the user has not approved. The L2 retrieval layer needs @kenz1117/dsh-engram installed separately, and the engine runs on Windows only.

Gives agents the DSH (Cordis) plugin authoring contract and the dsh plugin market submission process, from the bundle manifest and entry module to the pull request.

Sorts every loaded skill into one or more user-owned workspaces in a right-sidebar tab: each workspace is its own category list plus where every skill sits, categories are created, renamed, reordered and deleted in place, and skills are dragged or picked between them. A first run can let the profile model build the first classification, or place skills into categories the user built first; clicking a row copies its /skill-name and hovering unfolds the description the skill ships.

Agent skills: browse, toggle and edit skills in the management page, and let the agent write new ones itself.

Skill panel for the DSH Web GUI: lists every installed skill with Chinese annotations and eight category filters, runs pinyin and fuzzy search, ranks by pin and recency, and manages each skill in place (pin, disable, reveal, uninstall with undo). Ships its own maintenance skill.

A fork of Microsoft's official .NET/C# skills for AI coding agents, additionally packaged as a DeepSeek Harness plugin — covering development, testing, diagnostics, migration, and AI integration.

Shows which skills each turn invoked and installs, updates or removes skills inside the app.

Extract Bilibili platform/AI subtitles or external/embedded/ASR/OCR fallback and render Markdown, Word, PDF, TXT, SRT or JSON with timestamps, bilingual alignment and a quality report. Requires Python 3.10+; platform/AI subtitles need a Bilibili SESSDATA cookie; OCR/ASR/PDF need ffmpeg, faster-whisper and LibreOffice or reportlab.

Interior and exterior ballistics paper reproduction and code generation skill. Requires LibreOffice Kit for PDF rendering and a vision API key (e.g. Qwen-VL) for formula OCR.

Tag-based skill filtering: attach tags to DSH skills, then hand each workspace or conversation only the subset its boolean tag expression selects (for example `pdf + docx` or `aegis * plugin`). Excluded skills are deny-shadowed out of the model catalog rather than merely hidden in the settings UI; skills outside the expression can still be added by hand or force-disabled, and the bundled `tagging-skills` teaches the agent to derive a tag set from the machine it is running on.

Installs the codex-cua skill so DeepSeek Harness can use Codex computer use: drives Chrome and native macOS apps through the runtime bundled with the ChatGPT/Codex desktop app, ships a persistent session client and a doctor self-check. Requires the ChatGPT/Codex desktop app with its Chrome extension, Python 3.9+, and macOS.

Composes tools, skills and MCP servers into switchable per-session sets, shrinking the resident tool surface and the system prompt on demand.

Motion graphics from a dsh session through the Miran Fann engine over MCP, with a Miran settings page and motion-design skills. Requires the Miran Fann engine installed separately (npx miran-fann setup) and a signed-in install.

Gowin (高云) 1.9 FPGA toolchain control for dsh: 15 tools covering environment and license probe, .gprj/.cst project and constraint auditing against a real GW1N board pinout, gw_sh batch synthesis and place-and-route, pnr resource and timing report parsing, programmer_cli JTAG scan and flash, arbitrary gw_sh Tcl, and the GAO on-line logic analyzer capture chain — plus a bundled gowin-fpga skill and three field-note references. Pure JS, zero runtime dependencies.

AI research toolkit for DSH: a model release radar, a per-model benchmark and community report from 13 structured leaderboards plus Chinese and English community discussion, and an AI news radar over 46 feeds and 22 official X accounts; registers four tools and three skills and renders every report to Markdown with a generated table of contents.

Bridges the Cua Driver MCP server into DSH: installs the cua-driver executable when it is missing, starts it over stdio through the in-box MCP client, and registers its 60 accessibility-first window, input, menu, and browser tools with a bundled workflow skill and one-time macOS permission guidance.

Read-only inventory of every agent preset for the Web GUI, with a matrix of which preset holds which tools, MCP servers and skills, plus CLIs that move a plugin between presets.

Reads the installed plugins, MCP servers and skills, groups them by capability, and reports which preset each belongs in; can register one preset per category on request.

Connects DeepSeek Harness to the official Vercel MCP server over OAuth, with per-Agent on-demand tool loading, slimmed tool schemas, paged long results and 34 bundled Vercel skills.

Use your ChatGPT account to bring Codex models into DSH: choose models and thinking effort, chat with images, use tools and skills, approve local tasks, answer interactive questions, continue and compact long conversations, check quota and Token history, and maintain a supported Windows screenshot helper.

Estimates what is filling the context window — per instruction file, per skill and per tool result — with a bloat verdict and actionable suggestions.

Interactive cards in replies, built from a fixed catalog of 31 components (sliders, inputs, sortable tables, charts, function plots, typeset formulas, tabs, checklists, flowcharts, quiz buttons, an animation player): controls recompute in the browser without another model call, and the model never writes HTML or JavaScript. Includes a calculus engine (integrals, derivatives, limits, sums, roots, Taylor polynomials) and a bundled skill that teaches the model when to use a card.