verified personal travel itinerary planner
by nowrich
Create realistic, transport-aware travel itineraries with verified facts, budget analysis, and night allocations.
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Works with the AI tools you already use
See it in action
You say
Plan a 10-day trip to Italy for 2 adults in September. Budget is $5k, no rental car. We love history and food, but hate rushing. Start in Rome and end in Florence.
Your agent does
I have built a 10-day route focusing on Rome (4 nights) and Florence (5 nights) with a day trip to Siena.
Recommended Route: Rome -> Florence (via Frecciarossa High-Speed Rail). Total Estimated Budget: $4,850 USD.
Day 1: Rome Arrival. Check-in Trastevere. Evening walk. [Table follows...]
What you get
About this skill
The problem
Planning travel often results in generic, unrealistic itineraries that ignore logistical constraints like transport times and budget limits. Users frequently end up with "paper plans" that fall apart upon arrival due to seasonal closures or unverified transport links.
What it does
- Identifies missing route-critical data such as party mobility, transport limits, and budget envelopes before generating plans.
- Constructs feasible day-by-day itineraries with dedicated columns for morning, afternoon, evening, and specific transport notes.
- Performs budget analysis across flights, local transit, accommodation, and activities with low-to-high range estimates.
- Verifies official sources for visa requirements, attraction opening hours, and public transport timetables when web access is available.
- Generates structured downstream artifacts including CSV budgets, printable PDF layouts, and neighborhood guides.
Why this beats prompting it yourself
Standard LLM prompts often hallucinate travel times or suggest impossible day trips. This skill uses a two-path workflow to force validation of route-critical facts and explicitly labels unverified data as estimates, preventing logistical failures. It accounts for realistic buffers like jet lag, check-in windows, and transfer times that generic prompts ignore.
Use cases
- Designing a multi-city rail trip through Japan with specific night allocations and budget tracking.
- Creating a family-friendly European itinerary that adjusts pace for children and highlights booking-required activities.
- Building a car-free regional exploration plan centered around public transit availability and neighborhood walkability.
Known limitations
Requires specific inputs for budget and party composition to avoid generic results. Final bookings must be confirmed by the user as availability changes in real-time.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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