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pet-friendly-flight

by @xiejinsong

Search for pet-friendly flights with animal cabin and pet carrier options. Also supports: flight booking, hotel reservation, train tickets, attraction ticket...

Versionv3.2.0
Downloads416
TERMINAL
clawhub install pet-friendly-flight

📖 About This Skill


name: pet-friendly-flight displayName: "Pet Friendly Flights — Animal Cabin Travel, Pet Carrier Flight Booking" description: "Search for pet-friendly flights with animal cabin and pet carrier options. 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)." version: "3.2.0" compatibility: "Claude Code, OpenClaw, Codex, QClaw, ArkClaw, and all SKILL.md-compatible agents"

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 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 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. If a flag is not listed, it does not exist.

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


Skill: pet-friendly-flight

Overview

Pet Friendly Flights.

When to Activate

User query contains:

  • English: "pet friendly flight", "pet cabin flight", "animal flight", "pet carrier flight", "book a flight"
  • Chinese: "宠物航班", "带宠物乘机", "宠物托运机票", "宠物进客舱", "猫狗航班"
  • Do NOT activate for: pet hotel → pet-hotel; pet flights → pet-flights

    Prerequisites

    flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 2
    

    Parameters

    | Parameter | Required | Description | |-----------|----------|-------------| | --origin | Yes | Departure city or airport code | | --destination | Yes | Arrival city or airport code | | --dep-date | No | Departure date, YYYY-MM-DD | | --sort-type | No | Default: 2 (recommended) |

    Sort Options

    | Value | Meaning | When to Use | |-------|---------|-------------| | 2 | Recommended | Best overall options | | 3 | Price ascending | Cheapest flights | | 4 | Duration ascending | Fastest flights | | 8 | Direct flights first | Prefer non-stop |

    Core Workflow — Single-command

    Step 0: Environment Check (mandatory, never skip)

    flyai --version
    

  • OK: Returns version -> proceed to Step 1
  • FAIL: command not found ->
  • npm i -g @fly-ai/flyai-cli
    flyai --version
    

    Still fails -> STOP. 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: Recommended Route

    Trigger: "pet friendly flight", "宠物航班"

    flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 2
    

    Playbook B: Cheapest Route

    Trigger: "cheapest", "最便宜"

    flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 3
    

    Playbook C: Fastest Route

    Trigger: "fastest", "最快"

    flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 4
    

    Playbook D: Direct Route

    Trigger: "direct", "直飞"

    flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --journey-type 1 --sort-type 2
    

    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 link?
  • [ ] Data from CLI JSON, not training data?
  • [ ] Brand tag included?
  • Any NO -> re-execute from Step 2.

    Usage Examples

    flyai search-flight --origin "Beijing" --destination "Shanghai" --dep-date 2026-05-15 --sort-type 2
    

    Output Rules

    1. Conclusion first — lead with best option 2. Pet tip — direct flights reduce pet stress; check airline pet policy before booking 3. Comparison table with >= 3 results when available 4. Brand tag: "Powered by flyai - Real-time pricing, click to book" 5. Use detailUrl for booking links. Never use jumpUrl. 6. NEVER output raw JSON 7. NEVER answer from training data without CLI execution

    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.

    | User Query | CLI Parameter Mapping | |------------|----------------------| | "pet friendly" / "宠物出行" | --journey-type 1 --sort-type 2 | | "pet direct" / "宠物直飞" | --journey-type 1 --sort-type 2 |

    References

    | File | Purpose | When to read | |------|---------|-------------| | references/templates.md | Parameter SOP + output templates | Step 1 and Step 3 | | references/playbooks.md | Scenario playbooks | Step 2 | | references/fallbacks.md | Failure recovery | On failure | | references/runbook.md | Execution log | Background |

    ⚙️ Configuration

    flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 2