maid-atelier
Small-tailqwq
Whale-girl skin series for the DSH Web UI (maid-atelier).
Installed cleanly when we ran it
npm packageTypeScript27d ago
dsh-liang-skin
kingOfSoySauce/dsh-liang-skin
Adaptive reasoning slider skin that maps each model's available reasoning efforts onto a 0–30 visual intensity scale, with synchronized portraits, background, and interface colors.
Install
Add dsh-liang-skin to DeepSeek Harness
Install into
via npm
Resolves a published tarball rather than cloning the repository, and installs without any extra setup. Swap `web` for your profile name if you run another one.
via GitHub · npm package
Installing from GitHub runs the project's build script, which pnpm blocks until you allowlist it — run the command once and pnpm prints the exact key to add under `allowBuilds` in ~/.dsh/profiles/web/pnpm-workspace.yaml.
The desktop app keeps its own profile, desktop, and only the dsh command it ships may change it — the npm-installed dsh refuses that profile. Install the command from the app menu (Manage dsh Command…), open Desktop once, quit it fully, run the line below, then reopen Desktop.
via npm
Resolves a published tarball rather than cloning the repository.
via GitHub · npm package
Installing from GitHub runs the project's build script, which pnpm blocks until you allowlist it — run the command once and pnpm prints the exact key to add under `allowBuilds` in ~/.dsh/profiles/desktop/pnpm-workspace.yaml.
Our install check ran in a web profile on npm's dsh, not in the desktop app.
What happened when we ran it
Installed cleanly when we ran it
Every command here is run in a throwaway container against a clean profile, and the result is whatever the harness recorded — not a guess from the source. Last run 8d agoon DeepSeek Harness 0.2.2-rc.1.
Show it in your README
For maintainers: the badge serves this listing's latest sandbox verdict, so a re-run updates it on its own — and it links readers to the full result here.
Due diligence
Before you install dsh-liang-skin
- Source of record: kingOfSoySauce/dsh-liang-skin — present in the community registry that DSH's own plugin market installs from.
- No licence file detected. Code without a licence is all-rights-reserved by default.
Security
What installing dsh-liang-skin runs
- Build scripts
No build script was blocked in our run.
Source: our sandbox install on DeepSeek Harness 0.2.2-rc.1, 8d ago.
- Install hooks
package.json declares no preinstall, install or postinstall script.
Source: package.json on GitHub, read at our last sync. prepare is not recorded; it runs only on a GitHub install, and shows up under build scripts when pnpm blocks it.
- README mentions
Neither shell commands nor credentials.
Source: a keyword match on the README — a hint about what the plugin touches, not an analysis of its code.
Not an audit. These are the record of one install and two text scans; nobody has read this plugin's code on your behalf. Plugins run with your agent's permissions.
The AI take
What it is — It maps each model's reasoning efforts to a 0-30 visual intensity scale with synchronized portraits, backgrounds, and interface colors for DeepSeek Harness.
Who it is for — It is suitable for users who need to switch between different reasoning efforts in DeepSeek Harness Web to optimize outputs. It is not suitable for users who only use native appearance settings, but from another angle: users who rely solely on single-step reasoning without adjustable efforts.
Watch out — It requires closing other skin plugins before installation to avoid conflicts. Sandbox testing passed and the plugin registered successfully in the profile. No obvious issues were found.
The verdict — I would install it if my tasks involve frequent reasoning effort adjustments in DeepSeek Harness, as it offers direct visual feedback; the value lies in making intensity changes intuitive.
Generated by grok-4.6, and a starting point rather than a verdict. Where it says a plugin installs or does not, that is from a real run in a clean profile — everything else is read off the repository. Trust the source over this.
What dsh-liang-skin does
dsh-liang-skin is a DeepSeek Harness plugin that turns the active model’s reasoning levels into a 0–30 visual intensity slider with matching portraits, backgrounds and interface colours.
DeepSeek Harness reads the current model’s reasoning.efforts rather than relying on fixed level names or counts. The plugin maps any number of available efforts evenly across 0–30, previews the visual state while dragging, then snaps to the nearest level when input ends. With binding enabled, it submits the selected effort’s original ID through the official ModelDirectory; the slider is hidden for models without reasoning support, models with only one selectable level, and addressed subagents. The liang-intensity-skin loader registers the client bundle, while the profile records the bundle in dsh.profile.bundles.
DeepSeek Harness loads the client skin in the Web profile, where it changes the interface appearance and stores the binding switch in the current browser’s local storage. Native light, dark and system themes can temporarily remove the skin. The bundled runtime includes 24 reviewed portrait anchors, so no separate asset download is required.
This is intended for users who want a visual control tied to model reasoning efforts. It is a poor fit when another skin is enabled, when appearance-only changes are required, or when the model has no usable reasoning levels. Web and official Desktop use separate installation profiles; Windows Desktop still lacks the repository’s real-device validation. No additional risk flags are detected.
dsh-liang-skin documentation
Configuring dsh-liang-skin
DeepSeek Harness registers the client bundle in the Web profile’s dsh.profile.bundles. The installed package is @leon___/dsh-client-liang-intensity-skin. The loader registration is exposed as liang-intensity-skin. The README also names ~/.dsh/profiles/web/package.json as the profile file and ~/.dsh/cordis.patch.yml as a patch file that may need checking for conflicts.
The appearance controls are under 设置 → 通用设置 → 外观:
滑动变祖enables the slider, portraits, background and adaptive colours.滑动变祖绑定思考等级controls whether slider changes are submitted to the model.- Native
浅色,深色and跟随系统remove the skin layer and slider for the current client activation.
The binding switch is stored in the current browser locally. Cross-refresh memory for the selected native appearance is not implemented.
Commands for dsh-liang-skin
DeepSeek Harness uses dsh plugin to add or remove the package from a profile. The Web profile is selected with --profile web; the command accepts a GitHub reference, a GitHub Release tarball, or a local path. A local-path installation can link to the cloned source directory. After source changes, run npm run build; the linked installation then uses the rebuilt lib/client.js after DeepSeek Harness restarts.
The documented removal command is dsh plugin --profile web remove @leon___/dsh-client-liang-intensity-skin. dsh --profile web --dump-config can be used to inspect the resulting configuration layer.
Requirements and platform notes
The README documents testing against DSH Web 0.1.7-rc.2 and user testing on macOS Desktop. Windows Desktop requires further real-device feedback. Web and official Desktop use separate profiles and installation paths. A running DeepSeek Harness instance must be restarted after installation or removal. The default Web port is 3080, which can be changed with --port.
Local development uses npm install, npm test, npm run build and npm run test:compatibility. Compatibility tests use an installed Chrome or Chromium; CHROME_PATH selects its executable and no browser is downloaded automatically.
Behaviour and known limits
Available levels come directly from reasoning.efforts. N levels are placed evenly from 0 to 30; dragging previews continuously, while pointer release, completed keyboard input or blur commits the nearest level. Binding disabled changes only appearance. Addressed subagents never show or submit the slider. The skin should not be combined with another enabled skin.
Written from the project's own documentation and kept in sync with it. Where the two disagree, the source is authoritative — read the README on GitHub
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