dsh-xiaohe-canvas
Run the following command in DeepSeek Harness:
dsh plugin install wild-River2016/dsh-xiaohe-canvas
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install wild-River2016/dsh-xiaohe-canvas in your terminal; the full source repository is at https://github.com/wild-River2016/dsh-xiaohe-canvas . Restart DSH after installation for the plugin to take effect.
About this plugin
E-commerce content creators typically juggle between canvas tools, AI generation APIs, and asset libraries, fragmenting their workflow and slowing production down. dsh-xiaohe-canvas bridges that gap by embedding Xiaohe Canvas directly into DeepSeek Harness conversations, so you can create, edit, and arrange nodes with natural language instead of manual dragging and page switching.
The plugin organizes its 42 tools across four pillars: canvas operations (creating, editing, deleting nodes, managing connections, exporting snapshots), an e-commerce template library spanning 16 categories from apparel to beauty to food with one-click import, multimodal AI generation for images, videos, audio, and copy, and a personal asset library. A built-in guided-dialogue skill proactively asks about your needs, matches templates, and auto-arranges nodes with layout and annotation notes, turning a rough idea into a finished piece in a single flow.
It is well suited for e-commerce operators, visual designers, short-video creators, and tech teams that want to weave canvas operations into an agent-driven automation pipeline.
Use Cases
- Create and manage canvas nodes via natural language to batch-produce product images and short videos
- Search apparel, beauty, and food e-commerce templates and import them into the canvas for rapid marketing assets
- Orchestrate image, video, and audio generation plus asset management within an agent conversation for end-to-end content workflows
Best For
- E-commerce operators and designers who need to mass-produce image and video content
- Tech teams aiming to integrate canvas operations into agent-driven automation pipelines
- Content creators using Xiaohe Canvas for AI-assisted creation
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