Itinerary builder

Itinerary Builder

This skill provides structured methodology for constructing multi-day travel itineraries that satisfy routing, temporal, and constraint requirements.

Itinerary Structure

A complete itinerary consists of:

{
  "plan": [
    {
      "day": 1,
      "current_city": "City Name",
      "transportation": "Self-driving: from A to B",
      "breakfast": "Restaurant name, City",
      "lunch": "Restaurant name, City",
      "dinner": "Restaurant name, City",
      "attraction": "Attraction1;Attraction2;",
      "accommodation": "Hotel name, City"
    }
  ],
  "data_sources": ["file1.csv", "file2.csv"]
}

Step-by-Step Building Process

1. Define Trip Parameters

Extract and validate:

• Start date and duration: Days 1-7 (March 17-23)
• Origin city: Minneapolis
• Destination cities: Three cities in Ohio (e.g., Cleveland, Columbus, Cincinnati)
• Budget: Total available funds and daily breakdown
• Constraints:
  • No flights (ground transportation only)
  • Pet-friendly accommodations required
  • Cuisine preferences: American, Mediterranean, Chinese, Italian
  • Party size: 2 people + 1 dog

2. Plan Route Sequence

For a 7-day trip visiting 3 Ohio cities:

• Day 1: Travel from Minneapolis to first Ohio city
• Days 2-4: Explore first city
• Day 5: Travel to second city
• Days 6-7: Explore second and third cities (or spread across remaining days)

Alternatively, create a loop route:

Minneapolis → City A (2 days) → City B (2 days) → City C (2 days) → Return/End

Calculate driving times between cities and ensure feasibility. Use distance data to estimate hours needed.

3. Allocate Budget

Break down the $5,100 total budget:

Accommodations: 6 nights × $80-120/night = $480-720
Meals (2 people): 7 days × $40-60/day = $280-420
Attractions: 7 days × $20-30/day = $140-210
Fuel/Transportation: Minneapolis→OH→Minneapolis ≈ $300-400
Contingency: 10% of above = $200-275
Total allocated: ~$1,500-2,025 (well within $5,100 budget)

Allocate remaining funds as buffers for higher-priced meals or attractions.

4. Select Accommodations

For each city/night:

• Filter for pet-friendly properties (essential constraint)
• Select options within daily budget allocation
• Verify availability for the specific dates
• Record property name and location

Note: Some datasets may label pet-friendly as:

• Boolean flag: pet_friendly: 1 or pet_friendly: true
• Text field: amenities: "pets allowed" or policies: "pet-friendly"
• Separate field: pets: "dogs welcome"

5. Schedule Meals

For each day, assign breakfast, lunch, and dinner:

Cuisine Distribution Strategy:

• Spread preferences across the week
• Mix cuisines: don't repeat the same on consecutive days
• Vary restaurant types: fine dining, casual, quick service

Example Schedule:

Day 1: American (breakfast), Mediterranean (lunch), Italian (dinner)
Day 2: Chinese (breakfast), American (lunch), Mediterranean (dinner)
Day 3: Italian (breakfast), Chinese (lunch), American (dinner)
...

Special Cases:

• Travel days (Days 1, 5): Light or quick meals
• Multi-hour drives: Include lunch options along route
• If a meal is skipped intentionally, use "-" as placeholder

6. Select Attractions

For each city day:

• Choose 2-4 major attractions relevant to city
• Vary types: museums, parks, landmarks, historic sites
• Consider proximity to accommodations (walking distance or short drive)
• Include 1-2 outdoor activities for pet-friendly vibes

Format: Separate with semicolon and trailing semicolon:

"Rock & Roll Hall of Fame;West Side Market;Cleveland Waterfront;"

7. Plan Transportation

For each day, specify:

Within-city: "Local exploration; pet-friendly walks"

Between cities:

"Self-driving: from Minneapolis to Cleveland (8 hours, ~500 miles)"
"Self-driving: from Cleveland to Columbus (2 hours, ~140 miles)"

Include rest stops and pet breaks for dog comfort.

8. Validate Constraints

Before finalizing, verify:

• ✓ All 7 days populated
• ✓ No flights used (only self-driving)
• ✓ All accommodations pet-friendly
• ✓ Budget stays within $5,100
• ✓ Cuisine preferences distributed
• ✓ Dates match (March 17-23, 2022)
• ✓ Exactly 3 Ohio cities visited
• ✓ All entries reference actual data sources

9. Generate JSON Output

Structure the final itinerary:

itinerary = {
    "plan": [day1, day2, ..., day7],
    "data_sources": [
        "background/citySet_with_states.txt",
        "accommodations/clean_accommodations_2022.csv",
        "restaurants/clean_restaurant_2022.csv",
        "attractions/attractions.csv",
        "googleDistanceMatrix/distance.csv"
    ]
}

import json
with open('/app/output/itinerary.json', 'w') as f:
    json.dump(itinerary, f, indent=2)

Common Pitfalls

• Travel time underestimated: Always add buffer for rest and pet breaks
• Repeating cuisine types: Track which cuisines used each day to avoid clustering
• Missing pet-friendly filter: Every accommodation MUST be pet-friendly
• Incomplete attraction data: Verify attractions exist in database before listing
• Budget overruns: Sum costs incrementally; recalculate after adding each item
• Incomplete daily entries: All fields (breakfast, lunch, dinner, attraction, accommodation) must be filled or explicitly marked as "-"

Iterative Refinement

If constraints cannot be satisfied:

1. Relax budget slightly if necessary (still within $5,100)
2. Adjust cuisine distribution if specific types unavailable in target cities
3. Modify city selection if Ohio cities don't have sufficient dining/attractions
4. Extend stay in some cities, shorten in others while maintaining 7-day total