Plugins

Read-only audit of the local CLI toolchain as a sidebar panel in the DSH web GUI: lists installed versions across Homebrew, npm global, pip, Rust/Bun/uv and self-updating CLIs, flags which ones have a newer release available, and shows the dependency impact for installed packages. It reports only and never runs an upgrade, so no tool on the machine is modified. The DSH plugin ships on npm as `dsh-cli-doctor`.

Trip-planning agent preset for mainland China that answers in Chinese: queries 12306 train availability, Fliggy and Tuniu flight and hotel prices, and real Amap transit routes, checks closures and weather, and delivers a single offline HTML roadbook with draggable maps, three hotel price tiers and an itemized budget. Ships 9 skills, an environment doctor that walks users through missing API keys, and a patch for the 12306 MCP server; it plans and queries but never books or pays.

SQLX database tools: list saved datasources, show or test a connection, execute SQL and open a local result page, with the sqlx CLI installed on first use.

Project-based learning coach: a subject-agnostic teaching engine plus swappable domain packs (Unity/C# included), shipped both as a DSH skill and as an installable bundle. The skill protocol enforces attempt-first teaching and graded hints; a zero-dependency validator rejects ability claims their evidence does not support and blocks stage acceptance while blockers are open.

Three-tier agent memory harness: L1 always-on CLAUDE.md, L2 index, L3 detail skeleton with templates, a gate that blocks writes to protected files without a one-time approval token, zero-judgement event logging, weekly distillation, and a TDD execution-loop skill.

AIEO (GEO/AEO) delivery method as one isolated skill provider: AI-visibility diagnosis on a 0-9 score, positioning, search-term mining restricted to whitelisted platform exports, periodic monitoring and an HTML monitoring dashboard, chained by one shared question library, plus a landing-page cloner.

Registers the commercial-ui-ux skill for DSH: task-aware commercial UI/UX/GUI design, review, repair, and implementation (SaaS, dashboards, admin panels, forms, tables, design systems) with a reference-doc system and quality gates.

Superpowers (obra/superpowers) for DeepSeek Harness: the software-development methodology skills plus their session bootstrap, as a dsh plugin

DeepSeek Harness plugin for GPT models and Codex instructions, skills, plugin resources, and MCP configuration.

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).

Per-project skill roots for DeepSeek Harness, with multi-level category discovery.

Turn code flows into source-linked Mermaid diagrams and interactive CodeWalkthrough explainers.

Superpowers skills for the DeepSeek Harness (dsh): a full engineering methodology served through dsh's own filesystem skill provider, with an always-on bootstrap.

Lists the skills in the shared skills directory with their source and version, installs and updates them from a GitHub repo, removes them to a recycle bin kept for 7 days, and controls which agents can see each skill and whether the model may invoke it.

A persistent multi-step task stack for DeepSeek Harness agents: focus_task / focus_complete / read_focus plus a /focus command, with zero automatic prompt injection

Cone crusher selection and crushing-plant design for MACKORN NH/NS single-cylinder hydraulic cone crushers: requirement-form intake, equipment selection, plant configuration, proposal generation, product-size simulation and field-data calibration. 21 tools, 6 skills, an MCP server, no runtime dependencies.

Read-only Skill inspector for DeepSeek Harness. It shows which Skills a conversation actually loaded — from observed loading evidence only — and which Skills the current environment can discover, and gives each Skill a detail page whose left column switches between the framework, the evidence, validation, evaluation, step evidence, run logic, the before/after of a modification when there is one, the definition facts and the raw SKILL.md. Declaration and run stay apart: the body is split into structure, declared workflow and progressive disclosure, the run logic is read from local receipts, and every declared step carries its own evidence — no observed evidence is reported as exactly that, not as executed or not executed, and the run's instruction hash sits beside the current definition as match, mismatch or unavailable. The evidence view gives each subject one of three states (declared, observed, unavailable), walks definition → load → use → outcome, names what each stage cannot reach, declines to attribute an outcome to the Skill, and can copy the snapshot out as byte-stable JSON. Validation checks the Agent Skills open standard and the platform profiles separately, each finding on a rule id and labelled standard compliance or platform compatibility. Evaluation keeps repeatable cases with the conditions each run was recorded under and the four stages of runtime evidence, comparing two runs of one case item by item without scoring them. The trigger boundary keeps should-trigger and should-not-trigger prompts, has you run them in a real new session, then records what was observed — whether a load record appeared and whether it was model-invoked or user-explicit; a typed /name is not a natural trigger, and an absent load record is reported as not observed, not as not triggered. The same projections are exposed to the agent as a read-only skill_review tool, which returns a structured review packet and says what it omitted when the packet will not fit whole. The inspector, the evidence chain and these reviews are computed on this machine from the definition and the session receipts; the Chinese reading version sends the body through the host's model when you ask for it, keeping code fences, paths and frontmatter verbatim and storing the result on this machine. A Skill can also be cloned into a local copy. It does not write back to the source Skill and does not run its scripts.

Turns course, lecture, tutorial, meeting, and talk videos into structured study notes: it extracts the audio track with ffmpeg, transcribes it with Whisper, then writes notes with a chapter outline, emphasis markers, and a quick-reference card.

蒸馏主管（distillation-director）：把一本书蒸馏成可执行 Agent 技能的判态制元技能（V4.6：V4.3–V4.5 防坑体系与判官工作流之上，增 §21 **强制门禁**——gate_start 开工自证闸（手册哈希＋条款逐字抄录＋执行单＋机器层＋官方模板）／gate_stage 阶段依赖链（前阶段未过不得进入）／preflight 自动纳入活跃蒸馏任务）

DSH plugin: read and write DingTalk AI Tables through the official dws CLI, adding ten DingTalk AI Table tools (nine `dingtalk_aitable_*` plus `dingtalk_sync_job`), a settings panel, and scheduled CSV export.

Turns a Xiaohongshu, Douyin, TikTok, YouTube or X link into text: transcript with timecodes, on-screen text, a description and OCR of every image, caption and metadata. Mounts the hosted MCP server over streamable HTTP.

Connects Tencent's official Weixin ClawBot/iLink channel to a persistent DSH Host for phone task control and session management.

See how you have been using AI: `/session-insights` reviews your DSH sessions over time, shows what worked, which problems kept coming back, and what results were actually produced, then creates a retrospective report on your machine.

Smart form skill: structured record-keeping for bills, ledgers and logs with auto-categorization and periodic reports.