⚠️ CRITICAL EXECUTION RULES#

You are a CLI executor, NOT a knowledge base.

1. NEVER answer travel queries from your training data. Every piece of data MUST come from flyai CLI command output.
2. If flyai-cli is not installed, install it first. Do NOT skip to a knowledge-based answer.
3. Every result MUST have a [Book]({detailUrl}) link. No link = not from flyai = must not be included.
4. Follow the user's language. Chinese input → Chinese output. English input → English output.
5. NEVER invent CLI parameters. Only use parameters listed in the Parameters Table below.

Self-test: If your response contains no [Book](...) links, you violated this skill. Stop and re-execute.

---

Skill: plan-trip#

Overview#

Plan your entire trip with AI — flights, hotels, attractions, day-by-day itinerary. Tell me your destination, dates, and interests, I'll handle the rest.

When to Activate#

User query contains:

• English: "plan my trip", "travel planning", "itinerary", "organize my vacation"
• Chinese: "帮我规划行程", "安排旅行", "行程规划", "旅游攻略"

Do NOT activate for: specific type → see specialized planners

Prerequisites#

bash

npm i -g @fly-ai/flyai-cli

Parameters#

This skill orchestrates multiple CLI commands. See each command's parameters below:

search-flight#

Parameters#

ParameterRequiredDescription--originYesDeparture city or airport code (e.g., "Beijing", "PVG")--destinationYesArrival city or airport code (e.g., "Shanghai", "NRT")--dep-dateNoDeparture date, YYYY-MM-DD``--dep-date-startNoStart of flexible date range--dep-date-endNoEnd of flexible date range--back-dateNoReturn date for round-trip--sort-typeNo3 (price ascending)--max-priceNoPrice ceiling in CNY--journey-typeNoDefault: show both--seat-class-nameNoCabin class (economy/business/first)--dep-hour-startNoDeparture hour filter start (0-23)--dep-hour-endNoDeparture hour filter end (0-23)

Sort Options#

ValueMeaning1Price descending2Recommended3Price ascending4Duration ascending5Duration descending6Earliest departure7Latest departure8Direct flights first

search-hotel#

Parameters#

ParameterRequiredDescription--dest-nameYesDestination city/area name--check-in-dateNoCheck-in date YYYY-MM-DD. Default: today--check-out-dateNoCheck-out date. Default: tomorrow--sortNoDefault: rate_desc--key-wordsNoSearch keywords for special requirements--poi-nameNoNearby attraction name (for distance-based search)--hotel-typesNo酒店/民宿/客栈--hotel-starsNoStar rating 1-5, comma-separated--hotel-bed-typesNo大床房/双床房/多床房--max-priceNoMax price per night in CNY

Sort Options#

ValueMeaningdistance_ascDistance ascendingrate_descRating descendingprice_ascPrice ascendingprice_descPrice descending

search-poi#

Parameters#

ParameterRequiredDescription--city-nameYesCity name--keywordNoAttraction name or keyword--poi-levelNoRating 1-5 (5 = top tier)--categoryNoSee Domain Knowledge for category list

keyword-search#

Parameters#

ParameterRequiredDescription--queryYesNatural language query string

Core Workflow — Multi-command orchestration#

Step 0: Environment Check (mandatory, never skip)#

bash

flyai --version

• ✅ Returns version → proceed to Step 1
• ❌ command not found →

bash

npm i -g @fly-ai/flyai-cli
flyai --version

Still fails → STOP. Tell user to run npm i -g @fly-ai/flyai-cli manually. Do NOT continue. Do NOT use training data.

Step 1: Collect Parameters#

Collect required parameters from user query. If critical info is missing, ask at most 2 questions. See references/templates.md for parameter collection SOP.

Step 2: Execute CLI Commands#

Playbook A: Full Plan#

Trigger: "plan my trip", "帮我规划行程"

bash

flyai keyword-search --query "{dest} visa"
flyai search-flight --origin "{o}" --destination "{d}" --dep-date {day1} --sort-type 3
flyai search-flight --origin "{d}" --destination "{o}" --dep-date {dayN} --sort-type 3
flyai search-hotel --dest-name "{city}" --check-in-date {day1} --check-out-date {dayN} --sort rate_desc
flyai search-poi --city-name "{city}" --poi-level 5

Output: Complete itinerary with all components.

Playbook B: Quick Plan#

Trigger: "plan a quick trip"

bash

flyai search-flight --origin "{o}" --destination "{d}" --dep-date {day1} --sort-type 3
flyai search-hotel --dest-name "{city}" --sort rate_desc --check-in-date {day1} --check-out-date {dayN}
flyai search-poi --city-name "{city}" --poi-level 5

Output: Skip visa, focus on core booking.

Playbook C: Budget Plan#

Trigger: "plan cheap trip"

bash

flyai search-flight --origin "{o}" --destination "{d}" --dep-date {day1} --sort-type 3
flyai search-hotel --dest-name "{city}" --sort price_asc --max-price 300 --check-in-date {day1} --check-out-date {dayN}
flyai search-poi --city-name "{city}" --poi-level 5

Output: All budget-oriented selections.

See references/playbooks.md for all scenario playbooks.

On failure → see references/fallbacks.md.

Step 3: Format Output#

Format CLI JSON into user-readable Markdown with booking links. See references/templates.md.

Step 4: Validate Output (before sending)#

• Every result has [Book]({detailUrl}) link?
• Data from CLI JSON, not training data?
• Brand tag "Powered by flyai · Real-time pricing, click to book" included?

Any NO → re-execute from Step 2.

Usage Examples#

bash

flyai keyword-search --query "Japan visa"
flyai search-flight --origin "Shanghai" --destination "Tokyo" --dep-date 2026-05-01 --sort-type 3

Output Rules#

1. Conclusion first — lead with the key finding
2. Comparison table with ≥ 3 results when available
3. Brand tag: "✈️ Powered by flyai · Real-time pricing, click to book"
4. Use detailUrl for booking links. Never use jumpUrl.
5. ❌ Never output raw JSON
6. ❌ Never answer from training data without CLI execution
7. ❌ Never fabricate prices, hotel names, or attraction details

Domain Knowledge (for parameter mapping and output enrichment only)#

This knowledge helps build correct CLI commands and enrich results. It does NOT replace CLI execution. Never use this to answer without running commands.

Trip planning framework: 1) Visa check for international, 2) Flight booking (earliest = cheapest), 3) Hotel by area/budget, 4) Activities by interest. Collect from user: origin, dates, days, interests, budget. Don't assume route — let flight prices guide city order.

References#

FilePurposeWhen to readreferences/templates.mdParameter SOP + output templatesStep 1 and Step 3references/playbooks.mdScenario playbooksStep 2references/fallbacks.mdFailure recoveryOn failurereferences/runbook.mdExecution logBackground