alliances
Airline alliance membership (Star Alliance, oneworld, SkyTeam) and cross-alliance booking relationships. Maps which loyalty…
Guided trip planning workflow. Asks destination, dates, travelers, class, and flexibility, then runs parallel flight/hotel search with cpp math and booking plan.
$ npx -y skills add borski/travel-hacking-toolkit --skill plan-trip --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/plan-tripContext preview
The summary Claude sees to decide when to auto-load this skill.
Guided trip planning workflow. Asks destination, dates, travelers, class, and flexibility, then runs parallel flight/hotel search with cpp math and booking plan.
name: plan-trip description: Guided trip planning workflow. Asks destination, dates, travelers, class, and flexibility, then runs parallel flight/hotel search with cpp math and booking plan. disable-model-invocation: true category: orchestration summary: Guided trip planner. The hero command for the toolkit. license: MIT
The user invoked this skill explicitly. Run a guided trip planning workflow that produces a concrete, opinionated recommendation with cents-per-point math, transfer paths, and a booking plan.
If the user already gave details in their prompt arguments, use those. Otherwise, ask in this order, one question at a time. Don't fire all the questions at once.
1. **Where?** Destination(s). Accept regions ("Scandinavia"), cities ("Tokyo"), or specific airports. 2. **When?** Departure month or date range. Note flexibility: "exact dates" vs "any week in March" matters a lot for award availability. 3. **Who?** Number of travelers, ages if children/infants. The toolkit supports infant pricing and seat configurations. 4. **What class?** Economy / premium economy / business / first. Default to economy if unstated. 5. **Trip length?** Number of nights at destination if applicable. 6. **Points or cash?** Three valid answers: "best of both" (default), "points only" (treat cash as last resort), "cash only" (skip award search).
After question 6, confirm the plan back to the user in one sentence and start the workflow.
Once you have the inputs:
1. **Load lessons-learned** first. Non-optional. Other skills depend on it. 2. **Load flight-search-strategy** for the canonical parallel search plan. 3. **Pull balances** via the awardwallet skill if the user's intent is points or "best of both" AND if balances aren't already in this session's context. Skip the pull if you already know them. 4. **Run cash search in parallel** via duffel, ignav, google-flights, and the relevant free MCPs (Skiplagged, Kiwi). 5. **Run award search in parallel** via seats-aero across ALL programs (never filter to one program upfront — see lessons-learned). 6. **Cross-reference** with transfer-partners and transfer-bonuses to find the cheapest currency you actually have. 7. **Apply points-valuations** to compute cents-per-point on each award option. 8. **Surface anything from award-sweet-spots** that matches this route. 9. **Check stopovers** if the destination involves a connection. Multi-city trips might unlock "two destinations for the price of one" via Aeroplan, Alaska, or Flying Blue. 10. **Show the math** in a markdown table. One row per option, ranked. Columns: program, miles cost, cash co-pay, total $ value, cpp, hold-before-transfer rule, recommendation. 11. **Pick a winner** with one-sentence reasoning. 12. **Show booking next steps** via booking-guidance: which program to call, hold rules, transfer timing, phone numbers if needed.
If the trip is more than just flights, mention these as available next steps in your closing summary (not as a question):
Don't dump all of these at once. Lead with the flight recommendation. Mention hotels/activities as concrete follow-up actions the user can ask for next.
AI-powered travel hacking with points, miles, and award flights. Drop-in skills and MCP servers for OpenCode, Claude Code, and Codex. Ask your AI to find you a 60,000-mile business class flight to Tokyo.
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