name: private-car description: "Hire a private car with driver for customized day tours — visit multiple attractions at your own pace without the hassle of public transport. 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 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: private-car

Overview

Hire a private car with driver for customized day tours — visit multiple attractions at your own pace without the hassle of public transport.

When to Activate

User query contains: - English: "private car", "hire car with driver", "chartered car" - Chinese: "包车", "包车一日游", "带司机"

Do NOT activate for: car rental → car-rental

Prerequisites

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

Parameters

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: Day Tour

Trigger: "private car tour"

flyai keyword-search --query "包车一日游 {city}"

Output: Full-day private car tour.

Playbook B: Half Day

Trigger: "half day car"

flyai keyword-search --query "包车半日游 {city}"

Output: Half-day private car.

Playbook C: Multi-Day

Trigger: "multi-day driver"

flyai keyword-search --query "包车多日游 {city}"

Output: Multi-day with driver.

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 keyword-search --query "包车一日游 杭州"

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.

Private car tour pricing: ¥500-1500/day depending on city and vehicle type. Includes driver (usually English/Chinese speaking), fuel, tolls. Does NOT include: entrance tickets, meals, accommodation for multi-day. Best for: destinations with scattered attractions (Xinjiang, Yunnan), groups of 3-5, travelers with mobility issues.

References

这个包车服务查询工具质量中等偏上，优势在于查询流程清晰、校验严格，能避免虚假信息。但存在一个明显的不足：配套的参考文档和模板文件不完整，可能导致查询结果不够准确或用户体验不一致。如果开发方能完善这些缺失内容，这个工具会变得更加可靠实用。总体而言，能用但有改进空间。