aradotso/trending-skills/jinguyuan-dumpling-skill

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Install

npx vskill@latest install aradotso/trending-skills/jinguyuan-dumpling-skill

SKILL.md

markdown
---
name: jinguyuan-dumpling-skill
description: AI Skill for 金谷园饺子馆 — query restaurant info, hours, delivery, Wi-Fi, and trigger Meituan queue-taking via MCP tools embedded in your AI coding agent.
triggers:
  -install jinguyuan dumpling skill
  -帮我安装金谷园饺子馆 Skill
  -query jinguyuan restaurant info
  -金谷园怎么排队
  -add meituan queue skill to my agent
  -金谷园几点开门
  -help me queue at jinguyuan dumplings
  -金谷园外卖怎么点
---
 
# 金谷园饺子馆 AI Skill
 
> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection.
 
An official AI Skill for 金谷园饺子馆 (JinGuYuan Dumpling Restaurant) — the beloved Beijing dumpling shop near BUPT. Once installed, your AI agent gains 5 MCP query tools plus an embedded Meituan queue-taking capability, letting users ask about the restaurant and even grab a queue number without opening any app.
 
---
 
## What This Skill Does
 
| Capability | Example Query | Mechanism |
|---|---|---|
| Restaurant info (location, hours) | "金谷园在哪？几点开门？" | MCP tool |
| Delivery service | "能送外卖吗？怎么点？" | MCP tool |
| Raw dumpling takeaway | "生饺子怎么煮？" | MCP tool |
| In-store Wi-Fi | "Wi-Fi密码多少？" | MCP tool |
| Latest announcements | "有什么新活动？" | MCP tool |
| **Meituan queue (take number, check progress, cancel)** | "帮我排个队，2个人" | Embedded sub-Skill |
 
---
 
## Installation
 
### Option 1 — Tell Your Agent (Recommended)
 
Paste this into your AI assistant:

帮我安装金谷园饺子馆 Skill，仓库地址：https://gitee.com/JinGuYuan/jinguyuan-dumpling-skill

 
The agent will clone the repo and place it in the correct Skill directory automatically.
 
### Option 2 — Manual Clone

Qoder

git clone https://gitee.com/JinGuYuan/jinguyuan-dumpling-skill.git \ .qoder/skills/jinguyuan-dumpling-skill

Cursor

git clone https://gitee.com/JinGuYuan/jinguyuan-dumpling-skill.git \ .cursor/skills/jinguyuan-dumpling-skill

Claude Code

git clone https://gitee.com/JinGuYuan/jinguyuan-dumpling-skill.git \ .claude/skills/jinguyuan-dumpling-skill

Windsurf

git clone https://gitee.com/JinGuYuan/jinguyuan-dumpling-skill.git \ .windsurf/skills/jinguyuan-dumpling-skill

Generic / other agents

git clone https://gitee.com/JinGuYuan/jinguyuan-dumpling-skill.git \ .agents/skills/jinguyuan-dumpling-skill

 
Any IDE/agent that discovers a `SKILL.md` in the Skill directory will auto-load it on next startup.
 
### Option 3 — GitHub Mirror

git clone https://github.com/JinGuYuan/jinguyuan-dumpling-skill.git \ .agents/skills/jinguyuan-dumpling-skill

 
---
 
## Repository Structure

jinguyuan-dumpling-skill/ ├── SKILL.md # Agent instructions + metadata (core file) ├── skill.json # Machine-readable config: MCP endpoints, tool definitions ├── scripts/ # Reserved for future scripts ├── references/ │ └── meituan-queue/ # Embedded Meituan queue sub-Skill (self-contained) │ ├── SKILL.md # Queue instructions and command reference │ ├── scripts/ │ │ └── mt_queue.py # Queue implementation script │ └── references/ │ └── meituan-passport-user-auth/ # Auth sub-Skill ├── README.md └── LICENSE # MIT

 
The **critical files** for agent operation:
- `SKILL.md` — loaded by the agent; contains all natural-language instructions
- `skill.json` — MCP endpoint URLs and tool schemas
- `references/meituan-queue/` — self-contained sub-Skill for live queue operations
 
---
 
## MCP Configuration (`skill.json`)
 
The `skill.json` defines the MCP server endpoints and tool list. Example structure the agent reads:

{ "name": "jinguyuan-dumpling-skill", "version": "0.3.3", "protocol": "MCP", "transport": "streamable-http", "mcp_server": { "url": "https://<cloudbase-endpoint>/mcp", "auth": "none" }, "tools": [ "get_restaurant_info", "get_delivery_info", "get_raw_dumpling_info", "get_wifi_info", "get_announcements" ], "embedded_skills": [ "references/meituan-queue" ] }

 
> The MCP server is hosted on Tencent CloudBase. No local server setup required.
 
---
 
## MCP Tools Reference
 
### `get_restaurant_info`
 
Returns location, hours, and branch details.

Example MCP tool call (via any MCP-compatible client)

import httpx

response = httpx.post( "https://<cloudbase-endpoint>/mcp", json={ "jsonrpc": "2.0", "method": "tools/call", "params": { "name": "get_restaurant_info", "arguments": {} }, "id": 1 } ) print(response.json())

{

"result": {

"name": "金谷园饺子馆",

"hours": "10:00 - 22:00",

"branches": {

"bupt": "杏坛路文教产业园K座南2层",

"wudaokou": "五道口东源大厦4层"

}

}

}

 
### `get_delivery_info`
 
Returns delivery platforms and ordering instructions.

response = httpx.post( "https://<cloudbase-endpoint>/mcp", json={ "jsonrpc": "2.0", "method": "tools/call", "params": {"name": "get_delivery_info", "arguments": {}}, "id": 2 } )

 
### `get_raw_dumpling_info`
 
Returns packaging options and home-cooking instructions for raw dumplings.

response = httpx.post( "https://<cloudbase-endpoint>/mcp", json={ "jsonrpc": "2.0", "method": "tools/call", "params": {"name": "get_raw_dumpling_info", "arguments": {}}, "id": 3 } )

 
### `get_wifi_info`
 
Returns current in-store Wi-Fi credentials.

response = httpx.post( "https://<cloudbase-endpoint>/mcp", json={ "jsonrpc": "2.0", "method": "tools/call", "params": {"name": "get_wifi_info", "arguments": {}}, "id": 4 } )

 
### `get_announcements`
 
Returns latest promotions and news.

response = httpx.post( "https://<cloudbase-endpoint>/mcp", json={ "jsonrpc": "2.0", "method": "tools/call", "params": {"name": "get_announcements", "arguments": {}}, "id": 5 } )

 
---
 
## Embedded Sub-Skill: Meituan Queue (`meituan-queue`)
 
The queue capability is a **self-contained sub-Skill** in `references/meituan-queue/`. It wraps Meituan's queue API via `mt_queue.py`.
 
### Supported Operations
 
| Operation | User can say | Script action |
|---|---|---|
| Check queue status | "现在排队情况怎么样？" | Query Meituan for table types + wait count |
| Take a number | "帮我排个队，2个人" | Confirm → call take-number API |
| Check progress | "我前面还有几桌？" | Query current position |
| Cancel queue | "取消排队" | Confirm → call cancel API |
 
### Authentication Flow
 
First-time use triggers Meituan account OAuth. The agent guides the user through the flow using the `meituan-passport-user-auth` sub-Skill in `references/meituan-queue/references/`. Credentials are cached for the session.

references/meituan-queue/scripts/mt_queue.py — usage pattern

Environment variables used by the script:

MEITUAN_ACCESS_TOKEN — set after OAuth, managed by the auth sub-Skill

MEITUAN_USER_ID — populated post-login

import os import httpx

MEITUAN_ACCESS_TOKEN = os.environ["MEITUAN_ACCESS_TOKEN"]

def get_queue_status(branch: str) -> dict: """ branch: "bupt" | "wudaokou" """ headers = {"Authorization": f"Bearer {MEITUAN_ACCESS_TOKEN}"} resp = httpx.get( "https://api.meituan.com/queue/status", params={"poiId": branch}, headers=headers ) resp.raise_for_status() return resp.json()

def take_queue_number(branch: str, table_type: str, party_size: int) -> dict: headers = {"Authorization": f"Bearer {MEITUAN_ACCESS_TOKEN}"} resp = httpx.post( "https://api.meituan.com/queue/take", json={"poiId": branch, "tableType": table_type, "partySize": party_size}, headers=headers ) resp.raise_for_status() return resp.json()

def cancel_queue(queue_id: str) -> dict: headers = {"Authorization": f"Bearer {MEITUAN_ACCESS_TOKEN}"} resp = httpx.post( "https://api.meituan.com/queue/cancel", json={"queueId": queue_id}, headers=headers ) resp.raise_for_status() return resp.json()

 
> **Important:** Queue operations are **real business actions**. The agent always asks for user confirmation before calling `take_queue_number` or `cancel_queue`.
 
---
 
## Common Agent Interaction Patterns
 
### Pattern 1 — Simple Info Query

User: 金谷园北邮店几点关门？ Agent: [calls get_restaurant_info] → 营业时间 10:00–22:00，北邮店地址：杏坛路文教产业园K座南2层

 
### Pattern 2 — Queue Flow

User: 帮我在北邮店排个队，3个人 Agent: [calls meituan-queue: get_queue_status("bupt")] → 当前可选桌型：2人桌、4人桌、大桌。前方等待：5桌。 请确认：为北邮店选择4人桌，3人就餐，帮您取号？ User: 确认 Agent: [calls take_queue_number("bupt", "4人桌", 3)] → 取号成功！您的号码：A-047，前方等待：5桌

 
### Pattern 3 — Check Progress

User: 我前面还有几桌？ Agent: [calls meituan-queue: check_progress] → 您当前排队号 A-047，前方还有 3 桌

 
### Pattern 4 — Cancel

User: 取消排队吧 Agent: 确认取消排队号 A-047？ User: 是的 Agent: [calls cancel_queue("A-047")] → 已成功取消排队

 
---
 
## Configuration Reference
 
| Variable | Required | Description |
|---|---|---|
| `MEITUAN_ACCESS_TOKEN` | For queue ops | Set by auth sub-Skill after OAuth |
| `MEITUAN_USER_ID` | For queue ops | Set by auth sub-Skill after OAuth |
 
No configuration is needed for the 5 MCP info tools — they are public, unauthenticated endpoints on Tencent CloudBase.
 
---
 
## Versioning
 
| Component | Version | Notes |
|---|---|---|
| jinguyuan-dumpling-skill | 0.3.3 | This Skill |
| meituan-queue (sub-Skill) | Independent | Versioned separately |
| meituan-passport-user-auth | Independent | Versioned separately |
 
Sub-Skill versions evolve independently. Updating one does not require updating the others.
 
---
 
## Troubleshooting
 
### Agent doesn't load the Skill after cloning
 
- Confirm the directory contains `SKILL.md` at the root level
- Restart your IDE or agent session — Skills are loaded at startup
- Verify the clone path matches your IDE's Skill directory (see installation table above)
 
### MCP tool calls return errors
 
- The CloudBase endpoint may be temporarily unavailable; retry after a moment
- Check `skill.json` for the correct endpoint URL (it may be updated in newer versions)
- Ensure your network can reach Tencent CloudBase services
 
### Meituan queue auth fails
 
- Delete cached tokens and restart the OAuth flow by saying: "重新登录美团账号"
- Ensure `MEITUAN_ACCESS_TOKEN` is not stale; the auth sub-Skill handles refresh automatically during a session
- If the OAuth window doesn't appear, check that your agent has browser/webview access
 
### Queue number taken but agent shows error
 
- The number may still be valid — check the Meituan app directly
- Call `get_queue_status` to verify current position before retrying
 
### Skill version mismatch

Pull the latest version

cd .agents/skills/jinguyuan-dumpling-skill git pull origin main

 
---
 
## Technical Details
 
| Item | Value |
|---|---|
| Protocol | MCP (Model Context Protocol) |
| Transport | Streamable HTTP |
| Hosting | Tencent CloudBase (云函数) |
| Language | Python |
| License | MIT |
| Primary repo | https://gitee.com/JinGuYuan/jinguyuan-dumpling-skill |
| Mirror | https://github.com/JinGuYuan/jinguyuan-dumpling-skill |

Security

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Source

Popularity

Repository stars
83
Repository forks
15
7-day trend score
22

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 30 Sep 2026, 29 days ago.

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