travel-data-querying
Querying travel planning datasets (cities, restaurants, accommodations, attractions, distances) for itinerary generation.
- License 许可
- MIT
- 最近更新
- 2026-10-02
- Stars
- ★ 93
- Forks
- 8
01 前言 Front Matter
- name
- travel-data-querying
- description
- Querying travel planning datasets (cities, restaurants, accommodations, attractions, distances) for itinerary generation.
03 SKILL.md 正文
Travel Data Querying
Dataset Structure
All data lives under /app/data/ with these files:
Cities
background/citySet_with_states.txt— Tab-separated:CityName\tStatebackground/citySet.txt— City names onlybackground/stateSet.txt— State names only
Restaurants
restaurants/clean_restaurant_2022.csv- Columns:
index, Name, City, Cuisines, Average Cost, Aggregate Rating - Cuisines is a comma-separated string (e.g., "Tea, Pizza, Indian, Seafood")
- Average Cost is per meal (numeric)
Accommodations
accommodations/clean_accommodations_2022.csv- Columns:
index, NAME, room type, price, minimum nights, review rate number, house_rules, maximum occupancy, city house_rulescontains constraints like "No pets", "No smoking", "No parties", "No children under 10", "No visitors"- Price is per night
Attractions
attractions/attractions.csv- Columns:
Name, Latitude, Longitude, Address, Phone, Website, City
Distances
googleDistanceMatrix/distance.csv- Columns:
origin, destination, cost, duration, distance costcolumn is empty for driving (only populated for flights)- Duration is human-readable (e.g., "3 hours 11 mins")
- Distance in km
Flights
flights/clean_Flights_2022.csv— Not used when flights are excluded
Querying Patterns
Find cities in a state
grep -i "ohio" data/background/citySet_with_states.txt
Find restaurants by city and cuisine
grep -i "cleveland" data/restaurants/clean_restaurant_2022.csv | grep -i "italian"
Find pet-friendly accommodations (exclude "No pets")
grep -i "cleveland" data/accommodations/clean_accommodations_2022.csv | grep -iv "no pets"
Find driving distances between cities
grep -E "^Cleveland,Dayton," data/googleDistanceMatrix/distance.csv
04 同仓库更多 Skills
object_counter
Count occurrences of an object in the image using computer vision algorithm.
travel-planning-workflow
Invoke this skill when performing travel planning. It defines a structured workflow for generating itineraries. Following this workflow is essential to ensure the final plan satisfies user requirements.
bundled-dataset-search-tool
invoke this skill when you need to perform database search for travel planning. This skill provides some useful pre-packaged tools to look up accommodations, attractions, cities, driving distance, flights, and restaurants from the bundled dataset.
glm-output
Output-processing guidance for GLM tasks. Especially useful after glm-basics and glm-calibration when you need verifier-matching metrics from output.nc and a final /root/metrics.json.
glm-calibration
Calibration guidance for GLM tasks. Often most effective after glm-basics has clarified the setup; glm-output is the companion skill for exact final metric computation.
glm-basics
A good starting point for GLM calibration tasks. Use to inspect glm3.nml, confirm how GLM runs, and identify the relevant files before moving on to calibration and output evaluation.