Travel Optimizer Trip Planner

Problem

When a trip depends on price, timing, transfers, refund policies, and child-ticket rules, comparing screenshots across platforms is hard to turn into an actionable plan. travel-optimizer targets that workflow, focusing on flight comparison, holiday off-peak timing, rail or driving alternatives, and family travel constraints.

How it works and limits

The skill first confirms origin, destination, dates, party size, and child ages. It then uses web_search to collect pricing signals from platforms such as Qunar, Ctrip, Fliggy, and airline websites, and uses web_fetch to read more detailed pages when needed. It also applies patterns from pricing-patterns.md, such as buying domestic flights 2-4 weeks ahead, favoring Tuesday or Wednesday departures over Friday, and starting holiday research earlier. The final output compares multiple options, including platform refund convenience, price transparency, and family suitability, rather than returning a single lowest price.

Limitations: it relies on public web data and cannot guarantee live inventory, final ticket price, or successful booking. Child ticket, baggage, and document rules can vary by airline, platform, and route. If the travel dates are close, treat the output as a comparison and itinerary baseline, then verify final pricing on the booking platform.