Qitian Dasheng: Cake, Snack, and Flower Ordering Assistant
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About this skill
Problem addressed
Qitian Dasheng is for engineers who want to connect a cake, snack, and flower ordering workflow to a conversational Agent. It turns the dangaoss workbuddy MCP JSON-RPC 2.0 calls, Chinese parameter transport, address selection, product specification validation, and order status lookup into a fixed sequence, so integrations do not repeatedly hand-write curl requests, guess field names, or unwrap double-layer JSON responses.
How it works
The core behavior is workflow orchestration. It first checks dgss_token.md for user_token, then reuses default_city and default_aid when available; city input is normalized to the “city” level. Address handling uses getAddrList and addAddrList. Product handling maps cakes, snacks, and flowers to cat_id values, calls sweets_lst, and presents a fixed six-column list. Before checkout, it validates spec_id against the specification name, calls getOrderaddr to generate a payment link, and extracts scene from the URL for getOrderStatus order queries.
Scope and cautions
The skill mainly covers ordering and order status lookup. It does not handle refunds, cancellation, logistics, or invoicing. The token must come from the current user, and dgss_token.md should be added to .gitignore. Checkout supports only a single spec_id. Field names are easy to mix up: use area for district, addr for detailed address, and 200 as the success code. On Windows, prefer Python script invocation to avoid curl Chinese parameter encoding issues.
Use Cases
- Operations staff ask an IM bot to fetch saved addresses for a city using a user token and let the user choose one.
- Support receives a cake order request and needs to map the category, search products, show specs and prices, and generate a payment link.
- A user sends an 8-20 digit scene code, and the system must treat it as an order credential and call getOrderStatus for status.
- Engineers debug Chinese parameters on Windows and prefer calling the dangaoss MCP endpoint through a Python script.
Best For
- Operations owners for product ordering workflows who need to connect saved addresses and category keywords to a conversational bot.
- Backend engineers building MCP or JSON-RPC integrations who need to handle nested JSON responses and field mapping.
- Developers maintaining internal purchasing assistants who need quick commands for repurchase, address changes, and token changes.
- Customer service platform leads for enterprise clients who need controlled responses for unsupported features such as refunds and logistics.
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