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<img src="assets/readme/hero.webp" alt="dsh-reasoning-effort brings a Codex-style model and reasoning-effort slider to DeepSeek Harness" width="1200">

dsh-reasoning-effort

A Codex-style model and reasoning-effort control, built directly into DeepSeek Harness.

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On first launch, the plugin adds a combined model control below the DSH composer. Open it to find the reasoning-effort slider, whose levels adapt to whatever the selected model exposes, above the familiar model picker. The plugin is enabled by default and stays synchronized with DSH's /model command.

First use in three steps

1. Install the plugin

#### Ask an agent to install it (recommended)

If your current agent can run terminal commands, send it this complete prompt:

Install dsh-reasoning-effort for the DeepSeek Harness web profile.

Run only these two commands and do not change any other profile:
dsh plugin add github:statem-li/dsh-reasoning-effort
dsh --profile web --dump-config

Confirm that dsh-reasoning-effort appears in the output, then report the result.
Do not stop or restart my running DSH process. Remind me to restart the DSH Web Host manually after installation.

The agent should report whether dsh-reasoning-effort appeared in the resolved configuration.

#### Install manually

Open PowerShell and run:

dsh plugin add github:statem-li/dsh-reasoning-effort
dsh --profile web --dump-config

main is currently versioned 0.5.0, matching the latest release tag v0.5.0. #main always installs the newest code (which may later include unreleased changes); replace #main with #v0.5.0 to pin this release.

2. Restart the DSH Web Host

The plugin loads when the Web Host starts. After installation, stop the current host, start it again, and refresh the DSH page.

3. Open the model control

1. Create or open a session. 2. Click the model-and-effort button below the composer. 3. Drag the thumb or click the track; release to snap to the nearest level. 4. Click the model row below the slider to enter DSH's native model list.

Your result should look like this:

<img src="assets/readme/themes.webp" alt="The reasoning effort selector running in DeepSeek Harness dark and light themes" width="1200">

Where the levels come from

The slider renders exactly the reasoning.efforts the selected model exposes in the DSH model directory — count, names, and order are the model's, and the plugin adapts automatically. A common three-level combination:

DeepSeek models typically expose off / high / max; GLM coding models (e.g. GLM-5.2) expose five levels: off / low / medium / high / xhigh. The slider submits effort values exposed by the selected model; it does not bypass model or deployment limits. When a model exposes fewer than two levels, or none at all, the menu shows "current model provides no reasoning-effort levels" — see the troubleshooting section below for how to declare them.

Effort guidance for custom providers

Built-in routes get their levels from the pi-ai catalog and the plugin never touches them. Only models you declare yourself in llm-pi-ai receive guidance:

1. Open the model menu. If the current model is your own declaration and the directory exposes no levels (or the declaration disagrees with the knowledge base), a View declaration guidance entry appears. 2. The panel shows the suggested levels (e.g. GLM-5.2 → minimal/low/medium/high) and a copy-ready complete entry YAML — including the - id: line, with your existing name/contextWindow/maxTokens preserved — plus the settings.yaml path. 3. Replace the matching - id: entry with the copied content (do not create a second llm-pi-ai: root) and save. DSH reloads automatically; if not, restart the Web Host and refresh.

Models the knowledge base does not know get an annotated template to fill from the endpoint's docs. Known-hostile gateways (e.g. Aliyun Bailian maas/dashscope.aliyuncs.com, which rejects the developer message role) get an explicit warning, because settings.yaml cannot override that behavior.

The built-in knowledge base covers GLM-5.2 (minimal/low/medium/high) and Kimi K3 (low/high/max). Add more models under the plugin's own settings namespace; user entries win over built-ins:

dsh-reasoning-effort:
  entries:
    - id: my-model
      provider: "*"          # provider route, * wildcard
      model: "my-model-id"   # model id, * wildcard
      note: description
      efforts:               # display level -> wire value the endpoint accepts
        low: "low"
        high: "high"
        max: "max"
      compat:                # openai-completions routes only
        thinkingFormat: "openai"
        supportsReasoningEffort: true

The plugin only provides snippets — it never writes configuration, and catalog-declared level sets (even a single level) are never flagged.

Enable the Big Fat Fish slider

The first installation uses the plain white thumb. To switch to the eight-frame runner:

1. Open Settings → General. 2. Find Big Fat Fish slider below Appearance. 3. Enable it and return to the model control.

<img src="assets/readme/settings.webp" alt="The reasoning effort and Big Fat Fish slider switches in DeepSeek Harness General Settings" width="1200">

The runner changes only the thumb artwork. Snapping, keyboard control, radiation effects, and model selection remain unchanged. It animates faster while dragging and freezes on a stable frame when reduced motion is enabled.

The Reasoning effort selector switch on the same page disables the complete enhancement without uninstalling it. DSH's built-in model selector returns immediately. Both preferences stay in the current browser.

What the plugin adds

• Direct pointer tracking — the thumb follows the pointer continuously and snaps only on release.
• Native dark and light themes — blue-violet-black in dark mode and progressively stronger blues on white in light mode.
• Left-only motion effects — waves, shock pulses, pixel radiation, particles, and trails remain behind the thumb.
• Shared DSH session state — the slider and /model command use the same session model directory.
• Automatic rollback — a failed update restores the last confirmed selection.
• No extra network behavior — no plugin telemetry, credential handling, or server-side storage.

Troubleshooting

The slider does not appear

Check that:

1. You restarted the DSH Web Host after installation. 2. Settings → General → Reasoning effort selector is enabled. 3. The selected model exposes at least two effort levels in the DSH model directory (see the next entry for models without any), and thinking is not disabled by the deployment.

A model declares no effort levels (e.g. GLM-5.3)

Models missing from pi-ai's built-in catalog carry no reasoning levels at all, and the menu shows "current model provides no reasoning-effort levels". Declare them in ~/.dsh/settings.yaml — for GLM-5.3 on a zai coding route:

llm-pi-ai:
  providers:
    zai-coding-cn:
      models:
        - id: glm-5.3
          name: GLM-5.3
          contextWindow: 1000000
          maxTokens: 131072
          reasoningEfforts:   # key = level shown on the slider, value = reasoning_effort sent to the API
            low: "low"
            high: "high"
            xhigh: "max"
          compat:             # the zai route's detection does not send reasoning_effort by default
            thinkingFormat: "zai"
            supportsReasoningEffort: true

Notes:

• Level names come from the DSH level vocabulary (off / minimal / low / medium / high / xhigh); values are the reasoning_effort spellings the endpoint accepts. Leaving off undeclared makes it unselectable, which suits models that cannot turn thinking off.
• Models already in the pi-ai catalog (e.g. GLM-5.2) inherit their levels automatically — no configuration needed.
• Once upstream catalogs include the model, the hand-written declaration can be removed; explicit entries always win over the catalog.
• Submitted levels are validated and dispatched by the host; the plugin never bypasses model or deployment limits.

Confirm that the plugin loaded

dsh --profile web --dump-config

The output should contain name: dsh-reasoning-effort.

Uninstall

dsh plugin --profile web remove dsh-reasoning-effort

Restart the DSH Web Host afterward. The native model selector will return automatically.

Compatibility

DeepSeek Harness is a developer preview. Upstream UI or service changes may require a matching plugin update.

Development

pnpm install
pnpm run check
pnpm pack

pnpm run check validates TypeScript and rebuilds both the host entry and browser module. See [design/visual-spec.md](design/visual-spec.md) for the complete interaction contract and [SECURITY.md](SECURITY.md) for vulnerability reporting.

License

[MIT](LICENSE) © HanaAyane