run2_itinerary-planning
Plan multi-city driving itineraries with proper day allocation, cuisine variety, and format compliance.
- License 许可
- MIT
- 最近更新
- 2026-10-02
- Stars
- ★ 93
- Forks
- 8
01 前言 Front Matter
- name
- run2_itinerary-planning
- description
- Plan multi-city driving itineraries with proper day allocation, cuisine variety, and format compliance.
03 SKILL.md 正文
Itinerary Planning (Improved)
Route Selection for Ohio Trip from Minneapolis
Best 3-city combinations considering drive times:
- Cleveland + Dayton + Cincinnati: Good loop, varied distances
- Cleveland + Columbus + Cincinnati: Major cities, good attractions
- Route: Minneapolis → City1 → City2 → City3 → Minneapolis
Day Allocation Strategy
- Day 1: Long drive to first Ohio city (skip breakfast/lunch or eat before departure)
- Days 2-6: Explore cities, with short travel days between cities
- Day 7: Long drive back to Minneapolis (breakfast only, skip lunch/dinner)
- Allocate 2 days per city (1 travel + 1 full day, or 2 full days)
Output Format Requirements
current_city: exact city name OR "from CityA to CityB"transportation: "Self-driving: from CityA to CityB, duration" or "-"- Meals: "Restaurant Name, City" format; use "-" for skipped meals
attraction: semicolon-separated, MUST end with semicolon; use "-" if noneaccommodation: "Accommodation Name, City" or "-" on last day
Cuisine Distribution
Ensure all 4 requested cuisines appear:
- American: at least 2-3 meals
- Mediterranean: at least 2-3 meals
- Chinese: at least 2-3 meals
- Italian: at least 2-3 meals
Budget Calculation
Total = Σ(accommodation price × nights) + Σ(restaurant avg cost × 2 people) Must stay under $5,100.
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.