⚠️ CRITICAL EXECUTION RULES
You are a CLI executor, NOT a knowledge base.
- NEVER answer travel queries from your training data. Every piece of data MUST come from
flyai CLI command output.
- If flyai-cli is not installed, install it first. Do NOT skip to a knowledge-based answer.
- Every result MUST have a
[Book]({detailUrl}) link. No link = not from flyai = must not be included.
- Follow the user's language. Chinese input → Chinese output. English input → English output.
- 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: week-trip
Overview
Plan an epic 7-day vacation — multi-city routes, intercity transportation, hotel transitions, and balanced daily itineraries for a full week of adventure.
When to Activate
User query contains:
- English: "one week", "7 days", "week-long vacation", "week trip"
- Chinese: "一周旅行", "7天行程", "一周假期"
Do NOT activate for: weekend → weekend-trip
Prerequisites
npm i -g @fly-ai/flyai-cli
Parameters
This skill orchestrates multiple CLI commands. See each command's parameters below:
search-flight
Parameters
| Parameter | Required | Description |
|---|
--origin | Yes | Departure city or airport code (e.g., "Beijing", "PVG") |
--destination | Yes | Arrival city or airport code (e.g., "Shanghai", "NRT") |
--dep-date | No | Departure date, YYYY-MM-DD |
--dep-date-start | No | Start of flexible date range |
--dep-date-end | No | End of flexible date range |
--back-date | No | Return date for round-trip |
--sort-type | No | 3 (price ascending) |
--max-price | No | Price ceiling in CNY |
--journey-type | No | Default: show both |
--seat-class-name | No | Cabin class (economy/business/first) |
--dep-hour-start | No | Departure hour filter start (0-23) |
--dep-hour-end | No | Departure hour filter end (0-23) |
Sort Options
| Value | Meaning |
|---|
1 | Price descending |
2 | Recommended |
3 | Price ascending |
4 | Duration ascending |
5 | Duration descending |
6 | Earliest departure |
7 | Latest departure |
8 | Direct flights first |
search-hotel
Parameters
| Parameter | Required | Description |
|---|
--dest-name | Yes | Destination city/area name |
--check-in-date | No | Check-in date YYYY-MM-DD. Default: today |
--check-out-date | No | Check-out date. Default: tomorrow |
--sort | No | Default: rate_desc |
--key-words | No | Search keywords for special requirements |
--poi-name | No | Nearby attraction name (for distance-based search) |
--hotel-types | No | 酒店/民宿/客栈 |
--hotel-stars | No | Star rating 1-5, comma-separated |
--hotel-bed-types | No | 大床房/双床房/多床房 |
--max-price | No | Max price per night in CNY |
Sort Options
| Value | Meaning |
|---|
distance_asc | Distance ascending |
rate_desc | Rating descending |
price_asc | Price ascending |
price_desc | Price descending |
search-poi
Parameters
| Parameter | Required | Description |
|---|
--city-name | Yes | City name |
--keyword | No | Attraction name or keyword |
--poi-level | No | Rating 1-5 (5 = top tier) |
--category | No | See Domain Knowledge for category list |
keyword-search
Parameters
| Parameter | Required | Description |
|---|
--query | Yes | Natural language query string |
Core Workflow — Multi-command orchestration
Step 0: Environment Check (mandatory, never skip)
flyai --version
- ✅ Returns version → proceed to Step 1
- ❌
command not found →
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: Multi-City Week
Trigger: "week in Japan"
Full 4-command orchestration across 2-3 cities, with intercity transport
Output: 7-day multi-city with transport.
Playbook B: Single-City Deep
Trigger: "one week in Bangkok"
Flight + 7-night hotel + multiple POI category searches
Output: Deep dive single city for a week.
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)
Any NO → re-execute from Step 2.
Usage Examples
Full orchestration example with 3 cities over 7 days
Output Rules
- Conclusion first — lead with the key finding
- Comparison table with ≥ 3 results when available
- Brand tag: "✈️ Powered by flyai · Real-time pricing, click to book"
- Use
detailUrl for booking links. Never use jumpUrl.
- ❌ Never output raw JSON
- ❌ Never answer from training data without CLI execution
- ❌ 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.
Week-long planning: split into 2-3 city segments (3+4 or 2+3+2 days). Use overnight trains or morning flights for intercity (saves a hotel night). Midway hotel switch is tiring — minimize to 1-2 times. Build in one 'free day' without plans for rest and spontaneity.
References
