DeepSeek Harness Plugin: dsh-reasoning-options - Automatically Populate Reasoning Level and OpenCode Go Routing Header
dsh-reasoning-options is a plugin designed for DeepSeek Harness (DSH), aiming to address issues where third-party gateway models cannot select reasoning levels and the OpenCode Go gateway lacks the Session header. The plugin automatically adds a reasoning intensity selector for all pi-ai models and automatically injects the request headers required by OpenCode Go. It persists configuration through the native API, supports hot reloading, and requires DSH 0.2.0-rc.2 or later.
Read Moredsh-plugin-effort-declare: Declaring Reasoning Effort Levels and Image Input for Manually Added OpenAI-Compatible Models
`dsh-plugin-effort-declare` is a DeepSeek Harness (DSH) plugin intended to solve the problem where manually added third-party models cannot declare `reasoningEfforts` (reasoning effort levels) and `input` (image input) capabilities. By adding a page under Settings, it writes these capabilities to the official namespace, thereby restoring the Effort selector and image upload functionality in the UI. The plugin is released under the MIT license and applies only to manually added models using the OpenAI protocol. Core features include configuring reasoning effort levels per model, declaring image input support, providing protocol dialect presets, and exposing version information. Installation requires DSH 0.1.2-alpha.2 or later; after installing via a terminal command, navigate to “Settings → Reasoning”
Read Moredsh-adaptive-reasoning: Reasoning Tier Slider for DeepSeek Harness Web GUI
`dsh-adaptive-reasoning` is a capability-aware reasoning-level slider plugin for the DeepSeek Harness Web GUI. It invokes a continuous slider panel when "Reasoning Level" is clicked, supporting 0-100 continuous dragging and snapping, and uses WebGL2 to render flame visual effects. The plugin can read model metadata, auto-complete missing reasoning levels, and is compatible with `models.dev` data. After installation, the process must be restarted, and some custom Relays may cause request failures if they do not support the `developer` role.
Read MoreDSH Native Effort Slider: A Model-Aware Reasoning Effort Control Plugin
`dsh-reasoning-slider` is a plugin that offers a minimalist UI solution, decoupling the model from the reasoning intensity while strictly respecting the model's actual levels. It supports model detection, low-overhead interaction, native styling, multiple color schemes, and keyboard controls. The project is no longer under active development and has been moved to a read-only archive, maintained as a community project. After installation, it can be enabled from the DSH settings menu; if you prefer native controls or the latest iterations, we recommend removing this plugin.
Read Moredsh-model-modes: Inference Modes and Provider-Native Fast Mode for DeepSeek Harness Web Composer
dsh-model-modes is an MIT-licensed plugin (v0.1.3) maintained by DTSFO, designed specifically for the DeepSeek Harness web composer. Its core goal is to add an explicit `Fast ON/OFF` toggle while preserving the reasoning configuration in DSH's official model selector. The plugin addresses the inconsistency of Fast/Priority request parameters across different providers, and strictly ensures that enabling Fast mode does not silently switch models, downgrade reasoning levels, or change providers. It injects provider-native fast parameters at the final `llm-pi-ai` boundary via `AsyncLocalStorage`, supporting `Max + Fast` and `Ul
Read Moredsh-reasoning-slider: Switching reasoning gears within the DSH model selector
`qjcnmd/dsh-reasoning-slider` is an MIT-licensed DSH plugin designed to address the cumbersome process of configuring reasoning levels when frequently switching models in DeepSeek Harness. This plugin embeds the reasoning level slider directly into the model selector overlay, allowing users to intuitively view supported levels upon selecting a model and switch them in real-time by dragging the slider, with changes taking effect upon release. Additionally, the plugin supports keyboard arrow keys and mouse wheel operations, automatically retaining the current level when switching models. If the target model does not support the current level, it automatically reverts to the default level, significantly reducing operational overhead. Before installation, ensure that `pnpm` and `dsh` are available in the environment, then add the plugin via the `dsh plugin` command from npm or GitHub, and restart the `dsh web`
Read MoreAutomatically adjust the inference gears of DeepSeek Harness in rounds with dsh-tool-turbo
dsh-tool-turbo is a DeepSeek Harness host plugin maintained by Electricitysheep. It accesses the agent/request waterfall and automatically selects reasoning_effort based on recent tool calls: simple read and write operations will be downgraded to low, while heavy tasks will be considered for upgrading the level, and the task itself does not need to be modified. The directory installation command is `dsh plugin add github:Electricitysheep/dsh-tool-turbo`. This article is cross-verified based on the directory page, GitHub README/source code and the official llm-deepseek adapter.
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