⚠️ 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: landmark-hotel#

Overview#

Find hotels closest to a specific attraction, landmark, or scenic spot. First verifies the POI, then searches hotels sorted by walking distance.

When to Activate#

User query contains:

• English: "hotel near", "close to", "walking distance", "next to"
• Chinese: "附近酒店", "旁边住", "离XX近", "步行可到"

Do NOT activate for: city-wide search → budget-hotel

Prerequisites#

bash

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

Parameters#

ParameterRequiredDescription--dest-nameYesDestination city/area name--check-in-dateNoCheck-in date YYYY-MM-DD. Default: today--check-out-dateNoCheck-out date. Default: tomorrow--sortNoAlways distance_asc--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

Core Workflow — Dual-command#

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: City Landmark#

Trigger: "hotel near West Lake", "西湖附近酒店"

bash

flyai search-poi --city-name "{city}" --keyword "{poi}"
flyai search-hotel --dest-name "{city}" --poi-name "{official_poi_name}" --sort distance_asc --check-in-date {in} --check-out-date {out}

Output: Verify POI → search by distance.

Playbook B: Ancient Town#

Trigger: "stay in Wuzhen", "住在乌镇"

bash

flyai search-poi --city-name "{city}" --keyword "{town}"
flyai search-hotel --dest-name "{town}" --poi-name "{town}" --hotel-types "客栈" --sort distance_asc

Output: Inns inside the scenic area.

Playbook C: Theme Park#

Trigger: "Disney hotel", "迪士尼附近"

bash

flyai search-poi --city-name "{city}" --keyword "{park}"
flyai search-hotel --dest-name "{city}" --poi-name "{park}" --sort distance_asc

Output: Flag official partner hotels.

Playbook D: Nature Area#

Trigger: "hotel near Zhangjiajie"

bash

flyai search-poi --city-name "{city}" --keyword "{park}"
flyai search-hotel --dest-name "{city}" --poi-name "{park}" --sort distance_asc
# If <3 results → expand to city-wide

Output: Split: near park vs city center with drive time.

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 search-poi --city-name "Hangzhou" --keyword "West Lake"
flyai search-hotel --dest-name "Hangzhou" --poi-name "West Lake" --sort distance_asc --check-in-date 2026-05-01 --check-out-date 2026-05-02

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 detailUrl.
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.

POI ambiguities: 'West Lake' (Hangzhou vs Yangzhou), 'Great Wall' (Badaling/Mutianyu/Jinshanling), 'Disneyland' (Shanghai vs HK). Ancient towns: stay inside for authentic experience (客栈 > 酒店). Theme parks: official partners offer early admission. Nature areas: limited lodging near park, city hotels X min drive.

References#

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