Plugins

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.

Workspace-bound arbitrary file upload, reading, OCR, and rendering for DeepSeek Harness.

DeepSeek Harness out-of-tree plugin: give a text-only coding model eyes by routing images to a Qwen-VL (DashScope) route through ctx.llm and returning text.

Workspace-bound arbitrary file upload, reading, OCR, and rendering for DeepSeek Harness.

On-demand vision for text-only DeepSeek models: upload images, and the model calls a view_image tool backed by any OpenAI-compatible vision endpoint (Qwen/DashScope by default).

Local-first structured vision for text-only agents: images go to a local OpenAI-compatible VLM and come back as JSON evidence (summary, verbatim OCR, layout regions, entities/relations, colors, explicit uncertainty), with anti-hallucination fallback and an optional paste/upload bridge; zero cloud cost, images never leave the machine.

AX-first macOS computer use for DeepSeek Harness: accessibility snapshots with stable refs, background input, Unicode typing, menus and apps, set-of-mark screenshots, on-device OCR and verified actions — 11 tools bridged to the macos-cu CLI.

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.

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.

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.

FormatForge: forge 30+ file formats (PDF, DOCX, PPTX, XLSX, EML, EPUB, TOML, archives) into AI-readable text via a drag-and-drop inbox, ff_translate/ff_formats/ff_result tools and a CLI; scanned PDFs fall back to local OCR or an enhance hint for the session model.

Enhanced vision toolbox: 14 pixel-level vision tools (describe, ground, detect, crop, pixel-diff, OCR, long-screenshot OCR, vectorize, colors, cutout, screenshot, present, materialize, html-screenshot) driven by one OpenAI-compatible endpoint, with clean \[图片: path] bridge markers, content-safety classification and rate-limit auto-retry.

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

Local Windows 11 OneOCR tool for DSH: `oneocr_recognize` returns OCR text and structured line/word polygons, confidence, rotation, and handwriting style.

Local WeChat OCR tool for DSH: `wechat_ocr_recognize` returns recognized text and the engine structured result for a local image path.

KiroCrew bridge for DeepSeek Harness: let your dsh agent delegate to a persistent, self-evolving KiroCrew workspace over ACP (JSON-RPC 2.0 over stdio).

DeepSeek Harness OCR plugin — offline image text recognition powered by PaddleOCR-json (primary) and RapidOCR-json (fallback). 让 DeepSeek Harness 直接识别图片中的文字，无需视觉模型、完全本地离线运行。