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food-travel

by @zzzilin

Plan food-driven travel experiences — recommend best cities for a dish or cuisine, generate city food maps with meal-by-meal restaurant routes, and build com...

Versionv1.0.0
Downloads475
TERMINAL
clawhub install food-travel

📖 About This Skill


name: food-travel description: Plan food-driven travel experiences — recommend best cities for a dish or cuisine, generate city food maps with meal-by-meal restaurant routes, and build complete food-centric itineraries with flights, hotels, and dining schedules. Use when the user asks about food travel, food trips, eating tours, food guides, must-eat dishes, restaurant recommendations for travel, or phrases like "我想吃烤鸭去哪", "成都美食攻略", "3天吃遍西安", "周末广州美食游", "为了吃去旅行", "plan a food trip".

food-travel — Eat-First Travel Planner

> One-liner: Input a dish, a craving, or a city — get a complete travel plan built around eating.

This skill solves the full "eat → where → go → stay → route" chain for food lovers.

Scenario Detection

Identify which scenario the user wants, then follow the corresponding workflow:

| Trigger pattern | Scenario | Example | |----------------|----------|---------| | A dish/cuisine + no city | A: Pick a destination | "我想吃烤鸭" "想吃海鲜去哪" | | A city + food intent | B: City food map | "成都有什么好吃的" "杭州美食攻略" | | A city + duration + food intent | C: Full itinerary | "3天吃遍西安" "周末广州美食游" |

If unclear, ask the user to clarify.


Scenario A: Pick a Destination for Food

Input: a dish, cuisine, or flavor preference Output: best city recommendation + food list + travel logistics

Steps

1. Web search: "{dish/cuisine} 最正宗 去哪个城市吃" to identify the top 2-3 cities. 2. For each city, web search: "{city} 必吃 {dish} 餐厅推荐" to get restaurant data. 3. Search flights (if user provides origin):

   flyai search-flight --origin "{origin}" --destination "{city}" --dep-date {date}
   
4. Search hotels:
   flyai search-hotel --dest-name "{city}" --check-in-date {date} --check-out-date {date}
   

Output format

# 为了{dish},去{city}!

为什么选{city}

(One-paragraph reason)

必吃清单

| 餐厅 | 招牌菜 | 人均 | 地址 | 推荐理由 | |------|--------|------|------|----------| | ... | ... | ... | ... | ... |

怎么去

(Flight options table with booking links)

住哪里

(Hotel options near food districts, with booking links)


Scenario B: City Food Map

Input: a city name Output: meal-by-meal restaurant map organized by time of day

Steps

1. Web search: "{city} 必吃餐厅推荐" + "{city} 特色小吃 推荐" + "{city} 夜宵 推荐". 2. Organize results into 4 time slots: 早餐, 午餐, 晚餐, 夜宵/下午茶. 3. keyword-search supplement:

   flyai keyword-search --query "{city} 美食券 餐厅"
   
Filter for food-related items only.

Output format

# {city}美食地图

🌅 早餐

| 餐厅 | 推荐 | 人均 | 地址 | |------|------|------|------|

☀️ 午餐

...

🌆 晚餐

...

🌙 夜宵

...

可预订美食产品

(Filtered keyword-search results with images and booking links)

> 餐厅数据来自网络搜索,美食券来自 fly.ai 实时结果。


Scenario C: Full Food-Driven Itinerary

Input: city + duration (e.g. "3天吃遍西安") Output: day-by-day schedule with every meal planned + attractions between meals + transport + hotel

Steps

1. Web search: "{city} {N}天美食攻略" + "{city} 必吃餐厅推荐". 2. Search hotels:

   flyai search-hotel --dest-name "{city}" --check-in-date {date} --check-out-date {date}
   
3. Search flights (if origin provided):
   flyai search-flight --origin "{origin}" --destination "{city}" --dep-date {date}
   
4. Search attractions to fill between-meal time:
   flyai search-poi --city-name "{city}"
   
5. Organize into a day-by-day plan where every meal is the anchor.

Output format

# {N}天吃遍{city}

Day 1

🌅 早餐 — {restaurant}

  • 推荐:{dishes}|人均:{price}|地址:{addr}
  • ☀️ 上午 — {attraction}(吃完溜达消食)

    (POI info with booking link)

    🍜 午餐 — {restaurant}

  • 推荐:{dishes}|人均:{price}|地址:{addr}
  • 🌆 下午 — {attraction/activity}

    🔥 晚餐 — {restaurant}

  • 推荐:{dishes}|人均:{price}|地址:{addr}
  • 🌙 夜宵 — {restaurant}

  • 推荐:{dishes}
  • Day 2

    ...

    交通

    (Flight options with booking links)

    住宿

    (Hotel options with booking links, prefer hotels near Day 1 dinner area)

    预算估算

    | 项目 | 预估费用 | |------|----------| | 机票 | ¥xxx | | 住宿 | ¥xxx | | 餐饮 | ¥xxx | | 门票 | ¥xxx | | 合计 | ¥xxx |

    > 餐厅数据来自网络搜索,机票酒店来自 fly.ai 实时结果。


    General Rules

  • Food comes first — every itinerary section starts with a meal, attractions fill the gaps.
  • Web search for restaurants — flyai has no restaurant database; always use web search for dining data.
  • flyai for logistics — use search-flight, search-hotel, search-poi, keyword-search for transport, accommodation, attractions, and bookable dining products.
  • Always include booking links — for every flight, hotel, and POI result, show Click to book.
  • Always include images — show ![]({picUrl}) or ![]({mainPic}) when available.
  • Practical details — include price, address, opening hours when available.
  • Source attribution — "餐厅数据来自网络搜索,机票酒店来自 fly.ai 实时结果。"