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...
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
search-flight, search-hotel, search-poi, keyword-search for transport, accommodation, attractions, and bookable dining products.Click to book. or  when available.