Plugins

DSH 插件：将对话输入区的模型/推理强度入口替换为推理强度滑动条（兼容官方最新 DSH 与 DSH Desktop）

Forge quality gates for DeepSeek Harness: task gates, read-before-edit, bash hazard interception and quality scoring, enforced by the local forge CLI through DSH's typed interception points. Requires the forge CLI on PATH; without it the plugin fails open and says so with a best-effort notice at session start, and task gates also need forge init in the project.

Reads a running workbuddy2api-panel over its HTTP API and syncs its models into the DSH model picker with credit multipliers, CN/international realm labels and per-model reasoning-effort levels; also shows remaining credits and usage in a settings page and a sidebar badge.

Keeps the shared default model pinned, so switching the model inside a chat no longer rewrites the global default and no longer lowers that default's reasoning effort.

Fork of dsh-reasoning-effort with a two-level model picker in the composer: a provider list, a model pane that slides out beside it, search, and compact rows, alongside the reasoning-effort slider and its max-level effects.

Model channel auto-enricher for DeepSeek Harness: eliminates manually configuring contextWindow, maxTokens, \[text, image] multimodal input, and {low, high, max} reasoning effort tiers model by model after adding a provider channel, with live auto-enrichment on save, a Settings UI page, and timestamped backups.

DeepSeek Harness plugin for SuperGrok and X Premium subscriptions: device-code sign-in, the xai provider, account-visible chat models with context and per-million-token prices, reasoning efforts read from model capabilities, and subscription usage.

Predicts your next message after each turn and shows it as gray ghost text in the composer: Tab takes the whole line, Alt+Right takes one word at a time, Enter takes it and sends, Esc dismisses, and Alt+R asks the model again without repeating the old one. Typing a few characters completes from prompts already sent in the session, Up in an empty composer recalls the last one, and a plugin-page form sets the provider, model, reasoning effort, per-key toggles and generation limits.

Two-pane model picker that replaces the composer model menu with a searchable provider-grouped list on the left and a detail card on the right showing the selected model's context window, output cap, capability tags and reasoning-effort levels, all read from that model's own provider. The npm name dsh-model-picker belongs to another author; install through this GitHub source.

Runs the standalone opencode2api backend (jasonxu114514/opencode2api, Windows x64/ARM64, no Docker or OpenCode CLI) with DSH and on exit stops only the process it launched; its settings card installs, updates or rolls back the backend from checksum-verified GitHub releases, copies the initial admin password and syncs /v1/models into an opencode2api provider with context, vision and reasoning efforts, re-syncing every 10 minutes.

Reads each third-party endpoint's own model listing and keeps llm-pi-ai's per-model reasoningEfforts in sync, so the composer offers the thinking levels a model actually has.

Registers external ACP (Agent Client Protocol) agents such as Codex, Claude Code and Gemini CLI as DSH model providers: maps each agent's thought_level options to the reasoning-effort selector, forwards images when the agent advertises promptCapabilities.image, and routes permission requests to DSH's approval dialog; ships an ACP Agents settings page that imports Zed agent_servers JSON and discovers models.

Adds AMD Radeon Cloud as a model provider in DeepSeek Harness, with reasoning-effort levels declared per model. The provider definition ships in the plugin's own patch layer rather than in your profile.

Replaces the reasoning-effort dropdown with a draggable snapping slider, and draws 13 canvas effects across five style families (thrust, fluid, fantasy, tech, texture) with three tiers that unlock as the effort level rises. Custom mode combines 10 particle forms with 8 flow trajectories; 9 accent presets and a hex picker recolor every effect, and optional key sounds cover two voice clips, a synthesized duck squeak, a mechanical click and a local audio file.

DeepSeek Harness (DSH) 推理等级自动选择插件：由 Jev System One 模型判断每条消息值多少思考量，按模型声明的等级自动推导档位，上下文信封让「继续」这类追问继承话题深度，低置信度向上取，任何失败都静默沿用原等级。 | Jev-driven reasoning effort per message: per-model ladders derived from what each model advertises, a fixed-size context envelope so follow-ups inherit topic depth, ties break upward, silent fallback on every failure path.

A native reasoning-effort control for the composer: a blue-to-violet tier bar with a starfield and a sheen sweep. It owns the model seat and drives the official model-directories service, so the ladder comes from each model's own reasoning declaration and no other plugin is required.

Model capability editor: edit each model reasoning-effort levels and image-input (multimodal) declarations inline in the official model page, written back to settings.yaml as a whole group, with a floating entry as fallback when the anchor breaks.

Adds a Quick Chat entry to the Web UI sidebar that opens a floating chat window with its own model and reasoning-effort picker, optionally seeded with the current session's transcript, and keeps every side conversation in a resumable, renamable, deletable history.

Explicit model routing for Main, Subagents, web_search, and image generation, plus a catalog-driven Composer and Plan Review picker with Model, Effort, Context, Fast, and Thinking variants.

Configure default model routes for DeepSeek Harness subagents, with single-model, round-robin, random, and per-route reasoning-effort options.

Adds Claude, Gemini, and a local Ollama model to DSH's native model picker, using your existing Claude Code / Antigravity CLI logins instead of a metered API key, with a working reasoning-effort selector for Claude.

Pokémon-style skin for DSH Web with GBA frames, HP-bar status, effort level panel, and customizable color palettes.

Unified model routing for DeepSeek Harness: one logical ModelID over multiple providers with first-token failover and cooldown, health-aware candidate ranking, three tiers (tier1/tier2/tier3) auto-selected by purpose, per-candidate reasoning effort, and a settings-page management panel.

Reasoning-effort tier manager for custom API models plus cross-session preference memory: inline low/medium/high/max toggles inside Settings → Models, with atomic settings writes.