Discover The Best DSH plugins
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Find image understanding, screenshot analysis and visual interaction plugins; compare inputs and usage.
dsh-videogenAI video plugin for the dsh web GUI: multi-vendor video generation channels (OpenAI-compatible /v1/videos, Kling, MiniMax Hailuo, Volcengine ARK, custom generic async), FFmpeg video processing (probe / frame extraction / GIF / image compress), a lightweight storyboard studio (templates + shots + FFmpeg compose), Agent tools and a sidebar AI 视频 panel.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:shimingming520/dsh-videogendsh-vidgen-pluginMulti-provider AI video/image generation plugin for DeepSeek Harness (DSH). ComfyUI-style node canvas studio + multi-provider settings, with agent tools list_video_models / generate_video / poll_video_task. | DeepSeek Harness AI 视频/图片生成插件：多提供者、节点画布工作室、Agent 工具与 REST RPC。
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:xsluck/dsh-vidgen-plugindsh-view-image让 dsh 用独立的 OpenAI 兼容视觉模型读图：主对话历史只保留纯文本描述，图片字节不进上下文，纯文本模型也能读图。
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:johnoooooo/dsh-view-imagedsh-viminaDeepSeek Harness Cordis plugin: drive Vimina Windows GUI automation via stdio (serve/call). Registers 26 vimina_* tools (scan/click/input/key/VMA scripts/screenshot/window/mouse).
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:Sunse666/dsh-viminadsh-visibridgeHost-level vision bridge for text-only models: analyze_image tool (Ollama local / Xiaomi MiMo cloud / any OpenAI-compatible endpoint) returning structured evidence.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:lhbsaa/dsh-visibridgedsh-vision给纯文本模型自动配眼:图片消息自动桥接为视觉模型描述(日志内表面替换,不改写人类转录),附带 see_image 追问工具
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:237229953-create/dsh-visiondsh-visionGlobal upload + configurable vision recognition for DeepSeek Harness (DSH): a composer upload button in every session, automatic image recognition with a user-selected vision model, and fallback chain support.
dsh-visionDSH vision plugin: image recognition (Codex + Zhipu fallback) and generation (GPT Image + CogView fallback), text-only-model safe
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:HarryLi-7/dsh-visiondsh-visionDeepSeek Harness 识图插件：为 Agent 注册 image_analyze 工具，把本地图片或 URL 发送给 OpenAI 兼容视觉模型（默认 OpenRouter google/gemini-3.7-flash）并返回文字分析
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:joyiok/dsh-visiondsh-visionVision Bridge plugin for the DeepSeek Harness: routes attached images to a vision-capable model (default xiaomi/mimo-v2-omni) and feeds the text description back to text-only routed models such as DeepSeek.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:lakeofsky347/dsh-visiondsh-visiondsh-vision — a DeepSeek Harness plugin (tool template).
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:sjakdhasdh/dsh-visiondsh-visionGive DeepSeek Harness eyes: a vision_analyze tool that sends an image (local path or URL) to an OpenAI-compatible vision model and returns a text description.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:zoahdev/dsh-visiondsh-visionDSH Computer Use (vision + desktop control, auto-detects Windows native or WSL): see the Windows screen through the agent vision channel, drive mouse/keyboard with a Codex-style blue overlay (Esc to abort), plus a composer status pill.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:zzy6-a/vision-usedsh-vision-3090-fixLocal reverse proxy plugin for DeepSeek Harness that caps images per request to 1, for self-hosted vLLM backends that reject prompts with more than one image
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:pureexe/dsh-vision-3090-fixdsh-vision-adapter给 DeepSeek Harness 加视觉能力：可视化设置页选视觉厂商（Kimi/智谱/通义/OpenAI/Gemini/豆包/MiniMax/阶跃星辰）并粘贴 API Key，聊天里即可拖图识别——图片走视觉模型、文字走 DeepSeek 推理。
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:motongv/dsh-vision-adapterdsh-vision-androidVision + Android UI automation plugin for DeepSeek Harness: gpt-5.6-luna screenshot understanding and real-tap mobile app testing via adb
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:superclaude1/dsh-vision-androiddsh-vision-api-localorwebDSH 插件：可接入识图模型 API（本地大模型识图工具 + 设置界面）。配置 OpenAI 兼容的识图接口（LM Studio / vLLM / Ollama 等），接口留空即不启用识图模型。
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:TIPSONG/dsh-vision-api-localorwebdsh-vision-assistDeepSeek Harness 视觉助手插件：给没有视觉能力的模型配一个可随时切换的多模态识别模型。输入框图片自动落盘并改写为文本提示，主模型调用 vision_recognize 工具即可完成看图；识别模型在 settings 的 vision-assist 命名空间热更新切换。
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:wjling/dsh-vision-assistdsh-vision-benchVision 台架：会话区调试/上位机点表（按段添加地址），共享任务与时间线，并安装「台架模式」Agent 预设。
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:xingyingyuzhui/dsh-vision-benchdsh-vision-bridgeDSH 视觉桥接插件：复用 DSH Provider 或 OpenAI 兼容直连，支持可视化配置与图片粘贴
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:alaxrpg/dsh-vision-bridgedsh-vision-bridgeVision Bridge — a persistent DeepSeek Harness plugin that gives the text-only DeepSeek model image understanding by bridging to user-configured vision model APIs (OpenAI-compatible / Google Gemini).
dsh-vision-bridgeGive text-only DeepSeek Harness agents vision — multi-backend (OpenAI Vision API + CDP bridge), cross-platform, cached, configurable.
dsh-vision-bridgeDeepSeek Harness 多模态视觉桥：贴图自动转文字描述（llm/stream 代理）+ view_image/ocr_image 主动视觉工具 + 原生多模态路由自动跳过（rc.7 适配），让 text-only 的 DeepSeek 模型看见图片
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:DreamRift/dsh-vision-bridgedsh-vision-bridgeMinimal DSH vision bridge: capability-aware paste routing — image-capable models paste natively, text-only models get cached pastes as path markers read via vision_glance, so text-model sessions stay switchable
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:JochenYang/dsh-plugins#1fa9db8b12143f2af39d89a7b84b958b545e2b01&path:packages/dsh-vision-bridgeUse a feature keyword or category, then sort by recent updates or GitHub stars.
Read the description, AI analysis and original README to understand what a plugin does.
Review compatibility, dependency ranges and instructions, then copy the available install command.
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Open its detail page and check the installation section. Copy the command into your Harness environment when available, or follow the project README.