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dsh-new-year-shop

Web Tools Updated 2026.08.21

Run the following command in DeepSeek Harness:

dsh plugin install uckkk/dsh-new-year-shop

Paste the following prompt into your AI chat to install this plugin:

Run dsh plugin install uckkk/dsh-new-year-shop in the DeepSeek Harness terminal to install the plugin; the source repository is at https://github.com/uckkk/dsh-new-year-shop .

About this plugin

Approaching Spring Festival, Mid-Autumn, or any other family occasion, the shopping list tends to be sprawling—fresh and dried goods, couplets and decorations, alcohol and tea, snacks and nuts—juggling items across chats with family members is both tedious and error-prone. dsh-new-year-shop collapses that back-and-forth into a single parameterized call: describe your household size, taste preferences, and budget, and the plugin returns a structured preparation plan in seconds.

The plugin centers on one focused tool, new_year_shop. It does not scrape e-commerce sites or compare prices; its sole job is to turn the parameters you provide into an actionable checklist for the household. Under the hood it is written in pure Node.js with zero network dependencies, so it runs reliably in offline or resource-constrained environments and keeps the security surface minimal.

It is well suited for family members who plan one large shopping run each festival season, users who prefer getting a structured suggestion inside an AI conversation rather than opening a shopping app, and developers who want to model festival prep as a reusable, parameter-driven workflow.

Use Cases

  • Draft a complete New Year shopping list for the household days before the festival
  • Generate a quick ingredient and decoration plan before a Mid-Autumn family dinner
  • Produce an actionable preparation checklist in an offline environment

Best For

  • Family members who plan one large festival shopping run each season
  • Users who prefer structured suggestions in an AI chat over opening a shopping app
  • Developers who want to model festival prep as a reusable parameter-driven workflow