Plugins

Data sensitivity classification plugin that auto-identifies sensitive fields and classifies them into high/medium/low/public levels.

Data cleaning plugin for deduplication, format standardization and anomaly detection.

Data asset orchestration engine that chains suite tools into preset pipelines (masking, cleaning, inventory, packaging, attestation, AI dataset health check, government inspection, circulation assessment), with incremental and scheduled processing.

AI dataset quality inspector for annotation consistency, class distribution bias and data leakage detection.

HarmonyOS development suite for DSH: a right-sidebar HiLog inspector (live stream with level/logger/text filters) and an ArkUI Inspector (screenshot pick, collapsible component tree, node properties with search, box model), two tree sources — the DevEco debug channel (declared padding/margin/border and custom component names) and the uitest accessibility tree — an .ets viewer with ArkTS syntax highlighting, DevEco Studio/CLT toolchain and device management, plus the harmony_ui_tree agent tool. 21 remote methods, 82 unit tests.

Automated data masking tool based on national standards, automatically identifying sensitive fields like ID cards and phone numbers.

Data lineage tracking tool, mapping the full lifecycle of data to meet source legality requirements.

Quantitative data quality scoring based on GB/T 36344-2018, providing auditable quality reports for data asset capitalization.

PBR 3D model preview for game art: GLB/GLTF with textures, IBL environment lighting, orbit controls, and a material channel inspector (baseColor/normal/roughness/metallic/AO/emissive/wireframe); scalar channels shown as grayscale per PBR spec, via the pbr3d fence and pbr_render tool.

Read-only Web and Desktop profile health sidebar, masked credential readiness audit, and snapshot inspector for DSHGuard.

Installs an Orchestrator agent preset that plans and dispatches to model-pinned specialist subagents (explorer, oracle, librarian, designer, fixer, council), with named model profiles switched via an omoslim CLI and a Web inspector button showing the current subagent models.

Unified LLM request/response inspector: reasoning-effort tuning, external-think export, traffic & bundle analysis.

PC environment diagnostics & port control board: zero-dependency inspection of system, CLI toolchains, active listening ports with hover-to-kill release, and model key readiness. No external calls, zero plaintext secrets.

Renders HTML, React (JSX/TSX), Vue, SVG, Mermaid and Markdown written by the agent in an isolated iframe sandbox with SSE hot-reload, and adds a DOM click inspector, side-by-side visual diff, a responsive device matrix and one-click Vite ZIP export.

Page-level UI generation for DeepSeek Harness: design tokens (theme.json) and code standards (code-style.json) drive a dsh-fuse fence that renders whole pages, with spec pre-validation, a theme contrast guard, a pixel-level style inspector (getComputedStyle), undo history, and a settings UI.

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.

Real-time inspector of the files the agent reads and edits, with a file tree, in the DeepSeek Harness right sidebar: M/A/R badges, side-by-side diffs and live agent activity tracking.

Track the origin of local development ports on Windows and safely manage verified DSH services.

Runs the AI coding CLIs on your machine as a Tang-dynasty court: one tool drafts a plan, a second tool reviews or vetoes it, six ministries carry out the steps in parallel by dependency, an inspector checks each output and a final audit runs before you approve. Each task works in its own git worktree and branch and is merged only on approval. Supports Claude Code, Codex, Gemini CLI, Cursor CLI, OpenCode, Qwen Code, WorkBuddy and DSH itself via dsh headless, with a tool catalog that shows install commands. Also includes a task queue that splits a list into separate tasks, per-call token and cost accounting with budgets, and an English Roman Senate mode. Its HTTP routes have no DSH access check, so a web page open in your browser could call them.

Live preview tab for DeepSeek Harness: local server + WebSocket live reload, device frames, console error feed, point-and-ask DOM inspector.

Lists every system-prompt section, context block and tool schema assembled for a session with per-item token estimates, and lets you rewrite sections or hide tools for that session.

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.

Per-turn and per-step cost ledger for DeepSeek Harness: a Turns tab beside Chat and Trajectory with tokens, estimated cost, cache savings, and an inspector for tool arguments, raw results, and source. Client-only; prices are estimated from recorded model usage.

Flight recorder panel for DSH sessions: live monitoring, timeline replay with a tool waterfall and event inspector, per-agent cost attribution, and a cross-session cost overview.