dsh-better-model-selector
Run the following command in DeepSeek Harness:
dsh plugin install Khellendros97/dsh-better-model-selector
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install Khellendros97/dsh-better-model-selector in your terminal to install; source code is available at https://github.com/Khellendros97/dsh-better-model-selector
About this plugin
In the DSH chat composer, model selection and thinking intensity were crammed into a single nested menu. Once your model list grew, hunting for a specific option became tedious, and tweaking inference parameters meant backing out of the picker and diving back in. dsh-better-model-selector cleanly separates these two concerns into independent controls so every interaction is shorter and more intuitive. The model dropdown keeps its familiar form but gains live search and a favorite toggle, putting your go-to models one click away. Thinking intensity is redesigned as a slider, far more natural than tapping through discrete numbers. Ctrl/Cmd+P cycles through your favorite models and Ctrl/Cmd+T steps through intensity levels, keeping your hands on the keyboard for everyday switching. All state is shared with the /model command dialog, so a change in one place syncs instantly in the other.
Favorites are persisted at the host level via cookies, surviving session resets and port re-assignment after a DSH restart. On first load the plugin automatically migrates favorites from older cookie and localStorage keys, so an existing setup keeps working without manual re-entry. If you swap models frequently or have a precise feel for inference intensity, this plugin saves several redundant steps in your daily workflow.
Use Cases
- Model list is long and you need search to find a model quickly
- You prefer an intuitive slider over tapping numbers to set thinking intensity
- Favorites must survive restarts and port re-assignment without re-entry
Best For
- Frequent DSH users who switch between many models daily
- Developers who prefer keyboard-driven workflows and fewer mouse clicks
- Users who need persistent preferences and care about local data integrity
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