プラグイン

Local media/doc pipeline: ffprobe, extract, thumbnail, PDF, ASR, pandoc, OCR, exif (allowRoots include IM inbox).

Publishes a lesson into the DSH conversation: the dependency spine, the question and the vault's drawings, drawn in the vault's own palette.

Windows computer use forked from computer-user: 13 computer_* tools that read the screen and drive the mouse and keyboard. Image-capable routes get the screenshot as a real image with an exact image-to-screen mapping, so no external OCR; elements return as UI Automation refs so a click lands on the exact control rectangle; Ctrl+Alt+Esc stops every call.

Adds a markitdown tool that converts PDF, Word, Excel, PowerPoint, HTML, CSV, EPUB and URLs to Markdown, using a real Microsoft MarkItDown installation when one is reachable and a bundled dependency-free converter otherwise.

Point-and-shoot screenshot capture: a system floating window turns a new screenshot (or copied image) into an Obsidian note with comments and key-point marking, instant Tongyi Qianwen OCR, per-day merging, and an optional evening AI organization pass.

Local-first file conversion: 26 conversions across images, PDF (with OCR and experimental PDF→DOCX), data, audio/video and office docs; 7 tools, all local, no API keys.

Transparent multimodal routing for text-only models: every image in every model call is fully transcribed (verbatim OCR, data, uncertainty zones, injection-hardened) by your own multimodal understander, with focused re-look via vision_relook and automatic retry on image-related failures. No bundled endpoints, no borrowed logins.

Free vision OCR with adaptive tile recognition for long documents and Markdown/Word/PNG/Excel export.

DeepSeek Harness vision plugin: 8 analysis modes (describe, OCR, chart data, UI review, object detection, compare, code-gen, debug), any OpenAI- or Anthropic-compatible vision API, with a built-in free vision model and automatic rate-limit failover.

DeepSeek Harness 用のワークスペース限定の任意ファイルアップロード、読み取り、OCR、レンダリング機能。

DeepSeek Harness out-of-tree プラグイン：テキストのみのコーディングモデルに画像を理解させるため、Qwen-VL（DashScope）ルートを ctx.llm 経由でルーティングし、テキストを返す。

DeepSeek Harness 向けワークスペース連携任意ファイルアップロード、読み取り、OCR、レンダリング。

テキスト専用 DeepSeek モデル向けのオンデマンドビジョン：画像をアップロードすると、モデルが任意の OpenAI 互換ビジョンエンドポイント（既定は Qwen/DashScope）に支えられた view_image ツールを呼び出します。

テキスト専用エージェント向けのローカル優先の構造化ビジョン：画像はローカルの OpenAI 互換 VLM に送られ、JSON の証拠（要約、逐語 OCR、レイアウト領域、エンティティ/関係、色、明示的な不確実性）として返ります。ハルシネーション対策のフォールバックと任意の貼り付け/アップロードブリッジ付き。クラウド費用はゼロで、画像はマシン外に出ません。

Scene-awareness probe for DSH on macOS: a privacy-first, pull-model `look` tool that reads the frontmost non-self window (app info, AX title/selection, gated local OCR), plus a summon-hotkey snapshot captured the instant you press.

Personal-experience memory for DSH: turns solved tasks into sourced problem cases with condition-scoped claims, recalls them into new tasks via hidden pre-step injection, and makes corrections/deletes cascade to future recall.

Large-image recognition for vision-exp models: lossless 800×800 tile recognition (smart/pipeline/full), local OCR with preprocessing & handwriting routing, optional multi-vendor GPU (DirectML/CUDA/OpenVINO) with auto CPU fallback.

Local file upload: paperclip button and drag-and-drop, per-session storage under .dsh-uploads, and a read_document tool that pages text and OCRs images.

Apple on-device Vision tools for text-only dsh models: local OCR (zh-Hans + 30 langs), image classification, face detection, document layout, and a combined describe — 100% offline, no API key, tall-screenshot slicing.

Turns a Xiaohongshu, Douyin, TikTok, YouTube or X link into text: transcript with timecodes, on-screen text, a description and OCR of every image, caption and metadata. Mounts the hosted MCP server over streamable HTTP.

Drag-and-drop PDF, Office, images, and text/code files into DSH conversations. The host extracts (and OCRs) them into the prompt; attach_* tools cover notebook cells, PDF-page OCR, image describe, and save.

Lightweight, route-preserving vision link for DSH: a configured vision model sees while the selected text model stays in control.

Local eyes for text-only models: eyes_render draws text/shapes/Mermaid onto a canvas in the Web GUI, eyes_paste captures pasted images, eyes_ocr reads text via the built-in Windows OCR (offline), and eyes_analyze inspects pixels as structured data — no vision model required.

Paste images into DeepSeek Harness chat and have them read by a free local backend (macOS Vision / Tesseract) before the text-only DeepSeek model answers