플러그인

DeepSeek Harness 플러그인: 「推理等级」(reasoning effort) 단계 이름을 중국어로 번역하고, 연결된 커스텀 서드파티 모델에 추론 레벨 표시를 주입합니다(공식 DSH는 기본적으로 주입하지 않음). 선택한 단계는 아웃바운드 요청 본문에 기록됩니다.

DeepSeek Harness Standard를 위한 DeepSeek V4 첫 RL 앵커 플러그인으로, promotion 후 전체 기능과 Skill을 복원합니다.

DeepSeek Harness Web을 위한 조합 가능한 작업·추론·품질·사람 검토 자기진화 컨트롤.

DeepSeek Harness Web을 위한 조합 가능한 작업·추론·품질 컨트롤.

DSH Web GUI 모델 능력 구성: '설정 → 모델'의 모델 카탈로그 편집기에서 구성된 각 모델에 대해 이미지 지원 여부와 사고 수준(reasoning efforts)을 직접 설정하고 llm-pi-ai 설정 네임스페이스에 기록합니다.

DeepSeek Harness에서 추가 모델의 추론 강도(reasoning effort)를 선택할 수 있으며, 끄기(Off)와 5가지 표준 레벨을 제공합니다.

DSH 플러그인: 자동 듀얼 피어 Honcho v3 메모리, 컨텍스트 호출, 검색, 추론, 결론 및 상태 진단

비공식(사용자 정의) 프로바이더의 모델에 대해 추론 강도 수준, 컨텍스트 윈도, 출력 한도, 이미지 모달리티를 models.dev 데이터로 자동 채웁니다.

플로팅 추론 노력 슬라이더 팝업이 있는 공식 스타일 컴포저 모델 트리거.

Uses a configurable system-prompt section to request a chosen reasoning language (Simplified Chinese by default), and expands thinking rows by default while preserving rows the user manually collapses.

Remote DSH access that needs no hosting of your own — the Feishu DM chat is the interface over the bot's outbound long connection, with cards for workspace, session (switch and rename), model, reasoning effort, permission preset and balance, and tool approvals and agent questions answered in that same chat.

OpenRouter provider that reads the live /models list, so new models appear without a harness release: models sorted by name with input/output prices, per-model reasoning levels, image input, reasoning_details replay, Anthropic prompt caching, and actual spend per session including subagents from OpenRouter usage.cost, shown under the Web UI composer and by /cost.

Tiered compaction hub: replaces the single 80% compaction cliff with a configurable ladder (default 30/50/70/90) whose tiers escalate from gentle to maximum consolidation laws, folds a deterministic keyword index into every checkpoint so facts accumulate across cycles, and summarizes through a model chain — primary plus up to 3 fallbacks, each with its own reasoning effort. Adds a Compaction module sub-tab and a Settings card; toggling off always restores stock compaction.

OpenCode Go provider that verifies a model against the gateway rather than treating a recommendation as a measurement: the models.dev protocol suggestion is probed before it is used, reasoning levels follow a measured contract, and requests run through an ordered protocol fallback chain. Context window, max output and image-input numbers are declared by a runtime-refreshed models.dev layer rather than probed, with operator overrides above both. Several OpenCode Go credentials can be stored and switched from the settings page.

Wire-level LLM inspector: captures the raw HTTP request and response bodies of model provider calls and attributes each capture to the session that caused it through the llm/stream waterfall. The request pane renders the body as a collapsible tree with per-node sizes — one measured request was 98.6% a single 973-entry array — and the response pane reassembles the OpenAI-style SSE chunk stream into reasoning, content, tool calls and usage. Shown in a Conversation View tab and a loopback viewer page.

Telegram remote control for DeepSeek Harness: list conversations with titles and workspaces, resume paused persisted sessions on demand (preset remount), turn-tracked reply relay, first-line reasoning summaries, inline-button approve/reject with outcome edits, and a bot command menu.

A CSS skin that restyles the reasoning-tier control drawn by hytime/dsh-thinking-effort into a blue-to-violet pill with a starfield and a sheen sweep, with matching light and dark palettes. Requires that plugin to be installed; it adds no UI of its own.

Replaces the chat input model picker with a provider-grouped, collapsible list: groups models by provider, folds vision-bridge mirror providers back into their upstream, and carries the reasoning-effort options each model declares in settings. Tested on DSH Desktop only; the DSH web build is untested.

Zen Mode view tab and foreground time tracker for DeepSeek Harness: while the agent works, a calm conversation view shows running/done status, your latest user message, live activity hints and the final AI reply in markdown with one-line turn stats, plus screen-watching (focus) time tracking with daily/weekly Zen scores, a chat-hide toggle that hides tool calls and reasoning rows, auto enter/exit Zen on task start/complete, an Alt+Z shortcut and a Zen settings panel — pure client-side, stored in localStorage, no network.

Declare any number of LLM providers, each with its own endpoint, credential and per-model parameters (reasoning-effort vocabulary, image input, retry policy), across the OpenAI Chat, OpenAI Responses, Anthropic Messages and Google Gemini wire formats, configured from a settings page.

Codex-style DeepSeek Harness model and reasoning selector with model-advertised effort levels, DSH-native themes, left-clipped radiation effects, and copy-ready reasoning-effort declaration guidance for custom-provider models.

Sets the DeepSeek flash model's reasoning effort per step — thinking off for short cheap prompts, low for a plain request, high for engineering work — and raises it only on repeated tool failures. The model itself never changes; effort max is opt-in.

Smooth think-row experience for the DSH Web UI: think rows expand as a capped 24-line preview that glides to the bottom while reasoning streams, collapse with a short height animation on settle, and the main conversation view follows with a reader-safe smooth chase (no snaps, no yanks).

DSH plugin: resumes a turn that ended successfully with reasoning only, no text and no tool call, by sending one bounded follow-up