Dumpling Story Ordering Assistant

Problem

Many restaurant support details are scattered across group chats, printed menus, and staff memory. When customers ask about lamb and scallion dumplings, sour soup dumplings, barbecue hours, or invoices, responses can be inconsistent, incomplete, or speculative. This skill converts the Jiaozi Story store’s frequent customer questions into structured data, so a chatbot can answer menu, pricing, store, and hiring questions from stable facts.

How It Works

The core is to use shop_info, menu, dumplings, barbecue, and intents as the knowledge base:
- Menu lookup: Covers signature dishes, classic stir-fries, clay pots, vegetable dishes, soups, kids’ meals, dumplings, and barbecue, including specific prices and per-person ranges.
- Scenario-based recommendations: Trigger phrases such as “must eat” or “recommendations” return combinations like old-style braised chicken, kung fu carp, clay-pot Qingjiang fish, and lamb scallion dumplings.
- Store inquiries: Uses fields such as business_hours, address, phone, parking, and wifi to answer questions about hours, location, contact, parking, Wi-Fi, takeaway, reservations, payment, and invoices.
- Boundary rules: The hiring section is only triggered when the user explicitly asks; unknown questions should be handled reasonably but must not promise services that cannot be fulfilled.

Boundaries

This skill fits a single-store customer service scenario, especially for a location like Jiaozi Story (Gonggeng Road) with a clear menu and store profile. If it is extended to multiple stores, delivery platforms, dynamic inventory, or membership systems, additional data sources, permission controls, and real-time status checks are required; otherwise fixed answers may be mistaken for global service guarantees.