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.
- License 许可
- MIT
- 最近更新
- 2026-10-02
- Stars
- ★ 93
- Forks
- 7
01 前言 Front Matter
- name
- bundled-dataset-search-tool
- description
- 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.
02 资源文件 6
- 脚本scripts/search_accommodations.py3.4 KB
- 脚本scripts/search_attractions.py2.9 KB
- 脚本scripts/search_cities.py3.1 KB
- 脚本scripts/search_driving_distance.py5.6 KB
- 脚本scripts/search_flights.py4.2 KB
- 脚本scripts/search_restaurants.py3.5 KB
03 SKILL.md 正文
Overview
This skill provides six tools for searching the bundled dataset, always first use these tool scripts than writing code by yourself.
Installation
before using the tools, please install:
pip install pandas numpy requests
Tool 1 :Search Accommodations
Find accommodations for a specific city. The bundled script is located at scripts/search_accommodations.py. An Example:
from search_accommodations import Accommodations
acc = Accommodations()
result = acc.run("Seattle")
print(result)
Tool 2: Search Attractions
Query attractions for a given city. The bundled script is located at scripts/search_attractions.py. An Example:
from search_attractions import Attractions
attractions = Attractions()
print(attractions.run("New York"))
Tool 3: Search Cities
Map states to their cities from the background text file. The bundled script is located at scripts/search_cities.py. An Example:
from search_cities import Cities
cities = Cities()
print(cities.run("California"))
Tool 4: Search Driving Distance
Look up distance/duration between an origin and destination. The bundled script is located at scripts/search_driving_distance.py. An Example:
from search_driving_distance import GoogleDistanceMatrix
matrix = GoogleDistanceMatrix()
print(matrix.run("Seattle", "Portland", mode="driving"))
Tool 5: Search Flights
Filter the cleaned flights CSV for specific routes and dates. The bundled script is located at scripts/search_flights.py. An Example:
from search_flights import Flights
flights = Flights()
print(flights.run("New York", "Los Angeles", "2022-01-15"))
Tool 6: Search Restaurants
Query restaurants for a given city. The bundled script is located at scripts/search_restaurants.py. An example:
from search_restaurants import Restaurants
restaurants = Restaurants()
print(restaurants.run("San Francisco"))
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.
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.
d3js-visualization
Build deterministic, verifiable data visualizations with D3.js (v6). Generate standalone HTML/SVG (and optional PNG) from local data files without external network dependencies. Use when tasks require charts, plots, axes/scales, legends, tooltips, or data-driven SVG output.