dsh-commerce-cockpit
Run the following command in DeepSeek Harness:
dsh plugin install guannan1031/dsh-commerce-cockpit
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install guannan1031/dsh-commerce-cockpit in DeepSeek Harness to install this plugin; the source code is available at https://github.com/guannan1031/dsh-commerce-cockpit.
About this plugin
The dsh-commerce-cockpit is a DeepSeek Harness client plugin built for e-commerce operations teams who need a single, readable cockpit over sales, ad-spend, and inventory data that is otherwise scattered across multiple channels. It does not connect to any live marketplace and will never mutate ads, stock, prices, or orders on its own; instead it gives you a cockpit view to quickly reconcile numbers, surface missing fields, and export a one-page business brief.
The plugin ships with two data modes. Demo mode uses a fixed seed snapshot for zero-config exploration and teaching, while Imported mode reads user-supplied standard CSV files from a designated directory and displays only the fields that actually exist and pass validation. When product cost, refunds, platform fees, or other fields are absent, the relevant modules are explicitly labelled as not computable rather than being silently backfilled with demo figures. The rule-based QA endpoint (cockpit_ask) supports trend comparisons, channel-level analysis, and overall ad-spend-to-GMV ratio queries, and every result can be exported as Markdown alongside a data-integrity and missing-field report.
It is well suited to domestic multi-store e-commerce agencies performing daily morning checks and report reconciliation, as well as individual developers who want to prototype an e-commerce dashboard or verify metric definitions. Keep in mind that the current release does not include marketplace API integrations, automated task execution, or real competitor monitoring, and the overall ad-spend ratio reflects a simple GMV-to-ad-spend calculation rather than attributed advertising ROI.
Screenshots
Use Cases
- Daily morning check of sales, ad-spend, and inventory data across multiple stores
- Quick reconciliation to surface missing fields and non-computable metrics with a one-page brief
- Rule-based queries for trend comparisons and channel-level ad-spend ratios
Best For
- Multi-store e-commerce agencies in China
- Developers building e-commerce data dashboards
- Individuals validating metric definitions and data workflows
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