플러그인

현재 dsh 세션의 실시간 명령 체인과 프로젝트 스킬을 확인·관리, 그 자리에서 생성 및 편집 가능 — 보이는 그대로가 모델에 전달됨

DeepSeek Harness용 요청 컨텍스트 프로파일러 — 모델 요청 간 무엇이 바뀌었는지, 그리고 캐시 재사용이 그에 따라 어떻게 변화했는지 확인

DeepSee: DeepSeek Harness 비전, 멀티 모델 라우팅, 전달 전 Gemini 시각 자체 검증

텍스트 전용 DeepSeek Harness(dsh) 모델을 위한 플러그인 비전: 저가/무료 VLM 프리셋이 내장된 `vision` 도구, 다중 이미지 배치 분석, 붙여넣기로 힌트를 주는 이미지 수신, 핫 리로드를 지원하는 웹 설정 페이지

브라우저 Web Speech API 음성 입력: 서버 불필요, 키 불필요, 모델 다운로드 불필요(Edge=Azure, Chrome=Google 음성)

DeepSeek Harness용 재사용 가능한 Markdown 프롬프트 프로필, 턴별 모델 선택, 인자 치환, 상태 복원 지원

턴, 모델 단계, 도구 호출을 yiTrace로 내보내는 텔레메트리 백엔드

모델을 위한 세션 간 메모리: 과거 모든 세션을 전문 검색(ctx.sessionQuery를 통한 SQLite FTS5)하고 가장 잘 일치하는 발췌를 현재 컨텍스트로 가져옴

A floating VRM avatar with tool-driven expressions and VRMA animations, plus model and motion asset management.

Simulated FX trading arena played against an algorithmic whale-chan opponent: a live canvas candlestick chart over five instruments (EUR/TOKEN, GBP/TOKEN, TOKEN/JPY, gold, and Whale/TOKEN, her own coin she never shorts), selectable leverage from 10x to 500x, and two modes — a timed mode with 90s to 500s rounds settled on equity, and an untimed goal mode that starts with $300,000 and ends when someone first reaches $20M or goes into debt (equity below zero, no maintenance margin). The match runs in a module-level engine, so switching to a conversation does not stop it or restart it. Margin and spread are modeled, prices are a local random walk with occasional news shocks, and nothing touches the network or real money.

Map a remote server directory over SSH and SFTP into a controlled local cache workspace, so the model, agent, session and memory keep running on the local machine.

Pairs a phone console with the current DSH Desktop conversation. Running /phone shows a one-time QR code; after pairing the phone can send messages, approve tool calls, switch models and stop the task, while the desktop stays the only execution host. Requires AgentBridge running locally.

Redacts PII in tool-result text before it is logged (error-result metadata is not rewritten), denies read_image and binary/document reads outside allowPaths, provides local privacy_extract, privacy_ocr, privacy_scan and privacy_rehydrate tools (PDF/OCR needs a separately installed local extractor configured through extractCli), and enforces a fail-closed llm/stream egress guard before DSH dispatches any model request.

API key switcher for DeepSeek Harness: save multiple API keys in Settings and switch the active one; the next model request uses it, with no DSH restart.

Records a session as a run, replays it in an isolated workspace copy with another model or prompt, diffs the two trajectories side by side, aggregates runs into a task × variant matrix, and gates regressions with task assertions and a CI exit code.

Compare Git/SVN versions across repositories and export Chinese Markdown release reports with optional approved model analysis.

Keeps a model request alive through a dropped connection: transport failures retry until the network returns while real errors still fail fast, and a turn killed by a process crash offers a one-click, state-checking continuation.

Left-sidebar code review panel for DeepSeek Harness. Reviews local diffs, commits, or GitHub pull requests with the configured model using the Codex review rubric and P0-P3 findings. GitHub PR review requires a logged-in `gh` CLI.

Talk to DeepSeek Harness through Siri and iPhone Shortcuts: a bearer-key POST /siri endpoint on your computer answers each spoken request for Siri to read aloud, with a settings page (key, port, workspace, model, Agent Preset, rate limit, allowed addresses), optional DS Bot routing, and a ready-made Shortcut.

Hold Alt (default; rebindable in the plugin page) to dictate and insert a cleaned-up transcript, plus a sparkle button that rewrites the composer draft into a clearer prompt. Dictation requires the Harness Voice Input plugin with its SenseVoice model enabled.

Video study toolkit for DeepSeek Harness: fetch a public Bilibili single part or YouTube video, sample every 3 seconds plus change-triggered frames, transcribe locally with faster-whisper, page through section grids, and render a 16:9 study deck. Windows only, and needs the DSH pwsh tool plus Python 3.12 x64 with Pillow and FFmpeg/FFprobe; fetching adds yt-dlp, transcription needs faster-whisper with your own local model files, and deck output needs python-pptx.

Fusion 360 for DSH: bridges the MCP server Fusion ships (read, execute, update, electronics) with every upstream schema kept byte-for-byte while the always-on tool surface drops 70 percent, adds an editable endpoint under Settings, and wraps a local hf.py modelling loop as nine hf_* tools (needs Python 3.10+ and a fusion-harness workspace).

Layered memory for AI agents: five verbs (wake/work/pit/tomb/close), core layer read every time, archive on demand. Plain markdown, four pages created on first run; survives restarts, model swaps and plugin removal.

Restarts the DSH desktop host on macOS when a change needs it, then hands the conversation back to the same session with a note the model writes about why it restarted and what comes next.