⚠️ 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.

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Skill: photo-spots#

Overview#

Find the most photogenic and instagrammable spots — iconic viewpoints, colorful streets, architectural marvels, and hidden gems for your social media.

When to Activate#

User query contains:

• English: "photo spots", "instagrammable", "photogenic", "scenic viewpoint"
• Chinese: "打卡", "网红地", "拍照", "出片", "取景地"

Do NOT activate for: general attractions → top-attractions

Prerequisites#

bash

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

Parameters#

ParameterRequiredDescription--city-nameYesCity name--keywordNoAttraction name or keyword--poi-levelNoRating 1-5 (5 = top tier)--categoryNo--category "地标建筑" + "城市观光"

Core Workflow — Single-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: Landmarks#

Trigger: "photo spots"

bash

flyai search-poi --city-name "{city}" --category "地标建筑"

Output: Iconic landmarks and viewpoints.

Playbook B: City Walks#

Trigger: "instagrammable places"

bash

flyai search-poi --city-name "{city}" --category "城市观光"

Output: City observation and walking spots.

Playbook C: Art Districts#

Trigger: "art district photos"

bash

flyai search-poi --city-name "{city}" --category "文创街区"

Output: Creative and art districts.

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 "Shanghai" --category "地标建筑"

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.

Top photo cities in China: Shanghai (Bund, Yu Garden, French Concession), Beijing (Forbidden City, 798 Art District), Chongqing (Night views, Hongya Cave), Xiamen (Gulangyu), Dali (Erhai Lake). Golden hour (sunrise/sunset) gives best photos. Weekday mornings = fewer people in your shots. Use wide-angle for architecture, portrait mode for food.

References#

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