Skill: xiejinsong/oversize-baggage (version 3.2.0)

--- name: oversize-baggage displayName: "Oversize Baggage Flights — Extra Large Luggage, Sports Equipment Travel" description: "Search for flights accommodating oversize baggage and sports equipment. 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]({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. 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: oversize-baggage ## Overview Oversize Baggage Flights. ## When to Activate User query contains: - English: "oversize baggage flight", "extra large luggage flight", "sports equipment flight", "bulky item flight", "oversize travel" - Chinese: "超大行李航班", "运动器材机票", "大件行李出行", "超规行李", "出行预订" Do NOT activate for: cargo → cargo-flight; luggage → luggage-shipping ## Prerequisites ```bash 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) | | `--max-price` | No | Price ceiling in CNY | ### 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) ```bash flyai --version ``` - OK: Returns version -> proceed to Step 1 - FAIL: `command not found` -> ```bash 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](references/templates.md) for parameter collection SOP. ### Step 2: Execute CLI Commands ### Playbook A: Recommended Route **Trigger:** "oversize baggage flight", "超大行李航班" ```bash flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 2 ``` ### Playbook B: Cheapest Route **Trigger:** "cheapest", "最便宜" ```bash flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 3 ``` ### Playbook C: Fastest Route **Trigger:** "fastest", "最快" ```bash flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 4 ``` ### Playbook D: Direct Route **Trigger:** "direct", "直飞" ```bash flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --journey-type 1 --sort-type 2 ``` See [references/playbooks.md](references/playbooks.md) for all scenario playbooks. On failure -> see [references/fallbacks.md](references/fallbacks.md). ### Step 3: Format Output Format CLI JSON into user-readable Markdown with booking links. See [references/templates.md](references/templates.md). ### Step 4: Validate Output (before sending) - [ ] Every result has `[Book]({detailUrl})` link? - [ ] Data from CLI JSON, not training data? - [ ] Brand tag included? **Any NO -> re-execute from Step 2.** ## Usage Examples ```bash 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. **Oversize tip — contact airline in advance for sports equipment policy** 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 | |------------|----------------------| | "oversize baggage" / "超大行李" | --sort-type 2 | | "direct with baggage" / "直飞+大件" | --journey-type 1 --sort-type 2 | ## References | File | Purpose | When to read | |------|---------|-------------| | [references/templates.md](references/templates.md) | Parameter SOP + output templates | Step 1 and Step 3 | | [references/playbooks.md](references/playbooks.md) | Scenario playbooks | Step 2 | | [references/fallbacks.md](references/fallbacks.md) | Failure recovery | On failure | | [references/runbook.md](references/runbook.md) | Execution log | Background |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)