zoo-aquarium

Find zoos, aquariums, safari parks, and wildlife sanctuaries. Great for families and animal lovers. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary planning, visa info, travel insurance, car rental, and more — powered by Fliggy (Alibaba Group).

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Install skill "zoo-aquarium" with this command: npx skills add xiejinsong/zoo-aquarium

⚠️ 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: zoo-aquarium

Overview

Find zoos, aquariums, safari parks, and wildlife sanctuaries. Great for families and animal lovers.

When to Activate

User query contains:

  • English: "zoo", "aquarium", "safari", "animals", "wildlife"
  • Chinese: "动物园", "海洋馆", "野生动物", "水族馆"

Do NOT activate for: theme park → theme-park

Prerequisites

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 "动物园"

Core Workflow — Single-command

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: Zoos

Trigger: "zoo tickets"

flyai search-poi --city-name "{city}" --category "动物园"

Output: Zoos and wildlife parks.

Playbook B: Aquariums

Trigger: "aquarium"

flyai search-poi --city-name "{city}" --category "海洋馆"

Output: Aquariums and ocean parks.

Playbook C: Safari

Trigger: "safari park"

flyai search-poi --city-name "{city}" --keyword "野生动物园"

Output: Safari and drive-through parks.

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

flyai search-poi --city-name "Chengdu" --category "动物园"

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 zoos/aquariums: Beijing Zoo (pandas), Shanghai Wild Animal Park, Chimelong Safari (Guangzhou), Haichang Ocean Park (multiple cities). Panda bases: Chengdu, Dujiangyan, Qinling. Best for kids. Online tickets save 10-20%. Feeding times are the highlights — check schedule.

References

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

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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