tennis-grand-slam-planner

When a user mentions watching tennis, Grand Slam travel, or planning a trip to the Australian Open, French Open (Roland Garros), Wimbledon, or US Open, activate this skill. It combines the Grand Slam calendar with flyai travel APIs to generate a complete "match-chasing" itinerary — including flights, hotels near the venue, local attractions, and event tickets — all organized around the tournament schedule. Not for general travel planning without a tennis event context.

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Install skill "tennis-grand-slam-planner" with this command: npx skills add lokwq/ace-trip

Tennis Grand Slam Planner — Chase the Match Calendar

Plan a complete trip around any of the four tennis Grand Slam tournaments. This skill turns a simple intent like "I want to watch Wimbledon" into a fully structured itinerary with flights, stadium-adjacent hotels, match-day schedules, and pre/post-tournament sightseeing.

Prerequisites

  • flyai CLI must be installed: npm i -g @fly-ai/flyai-cli
  • Verify with: flyai keyword-search --query "tennis"

Workflow

Step 1 — Identify the target Grand Slam

Ask the user which tournament they want to attend (or infer from context). Read references/grand-slam-calendar.md to get:

  • Exact tournament dates, city, venue, and nearby landmarks
  • Which rounds fall on which days (so the user can pick specific matches)

If the user only says "the next Grand Slam", use date +%Y-%m-%d to determine the current date and find the nearest upcoming tournament from the calendar.

Step 2 — Determine trip parameters

Collect (ask if missing):

ParameterExampleRequired
Departure city"Shanghai" / "Beijing"Yes
Which rounds"Quarter-finals and on"No (default: full tournament)
Budget tier"mid-range" / "luxury"No (default: mid-range)
Extend for tourism"Yes, 2 extra days"No (default: no extension)

Map budget tier to price caps per references/travel-tips.md.

Step 3 — Search flights

Read references/flyai-commands.md for exact CLI syntax, then run:

flyai search-flight \
  --origin "{departure_city}" \
  --destination "{slam_city}" \
  --dep-date {arrive_date} \
  --back-date {leave_date} \
  --sort-type 3

Arrival rule: Plan arrival 1 day before the user's first target round. Departure rule: Plan departure 1 day after the user's last target round (or after the tourism extension).

Step 4 — Search hotels

Prioritize proximity to the venue. Run:

flyai search-hotel \
  --dest-name "{slam_city}" \
  --poi-name "{venue_name}" \
  --check-in-date {arrive_date} \
  --check-out-date {leave_date} \
  --sort distance_asc \
  --max-price {budget_cap}

Step 5 — Search event tickets and local experiences

flyai keyword-search --query "{slam_name} tickets {year}"
flyai keyword-search --query "{slam_city} tennis experience"

Step 6 — Search nearby attractions (if tourism extension)

flyai search-poi --city-name "{slam_city}" --category "{category}"

Select categories appropriate to the city from references/grand-slam-calendar.md.

Step 7 — Assemble the itinerary

Use the template in assets/itinerary-template.md to produce the final output. Read references/travel-tips.md for city-specific advice (transport, food, visa, weather gear) to include as practical tips.

The itinerary must follow this structure:

  1. Trip overview (tournament, dates, total budget estimate)
  2. Flight options (table with price, duration, airline)
  3. Hotel recommendations (top 3, with images and booking links)
  4. Day-by-day schedule (match days + rest/tourism days)
  5. Ticket and experience booking links
  6. Practical tips (visa, weather, transport, etiquette)
  7. Source attribution: "Based on fly.ai real-time results"

Output rules

  • All output in valid Markdown
  • Hotel images: ![hotel]({mainPic})
  • Attraction images: ![attraction]({picUrl})
  • Booking links: [Book now]({jumpUrl}) or [Book now]({detailUrl}) for hotels
  • Use tables for multi-option comparisons (flights, hotels)
  • Day-by-day schedule in chronological order
  • Emphasize key facts: dates, prices, distances to venue

Error handling

  • If no flights found for exact dates, widen the search window by +/- 1 day
  • If hotel results are sparse, remove --max-price and retry
  • If ticket search returns empty, suggest the user check the official tournament website and still complete the rest of the itinerary

Source Transparency

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