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Ancient Town Inn

该 Skill 要求执行 flyai CLI 调用飞猪实时数据,按目的地、日期、价格、星级、房型、关键词等条件搜索古镇与水乡中的传统客栈,并输出带预订链接的 Markdown 对比表;数据须来自命令输出,失败时按 fallbacks 处理。描述中还提及航班、酒店、门票等扩展场景,但正文未给出对应流程。

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热度 20.21
最近更新 2026-04-09 20:56:53
分类:生活依赖:代码执行 / 第三方 API应用场景:旅行 / 推荐

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add ancient-town-inn
Metadata
name
ancient-town-inn
description
Find traditional inns inside ancient towns and water villages — courtyard houses, wooden architecture, lantern-lit alleys, and old-world charm. 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
3.0.0
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: ancient-town-inn

Overview

Find traditional inns inside ancient towns and water villages — courtyard houses, wooden architecture, lantern-lit alleys, and old-world charm.

When to Activate

User query contains:

  • English: "ancient town inn", "traditional inn", "old town stay"
  • Chinese: "古镇客栈", "老镇住宿", "水乡客栈"

Do NOT activate for: modern hotel → budget-hotel-finder

Prerequisites

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

Parameters

Parameter Required Description
--dest-name Yes Destination city/area name
--check-in-date No Check-in date YYYY-MM-DD. Default: today
--check-out-date No Check-out date. Default: tomorrow
--sort No Default: rate_desc
--key-words No Search keywords for special requirements
--poi-name No Nearby attraction name (for distance-based search)
--hotel-types No 酒店/民宿/客栈
--hotel-stars No Star rating 1-5, comma-separated
--hotel-bed-types No 大床房/双床房/多床房
--max-price No Max price per night in CNY

Sort Options

Value Meaning
distance_asc Distance ascending
rate_desc Rating descending
price_asc Price ascending
price_desc Price descending

Core Workflow — Dual-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: Inn Inside Town

Trigger: "stay in ancient town"

flyai search-poi --city-name "{city}" --category "古镇古村" --keyword "{town}"
flyai search-hotel --dest-name "{town}" --hotel-types "客栈" --sort rate_desc

Output: Verify town → search inns inside.

Playbook B: Courtyard Inn

Trigger: "四合院客栈"

flyai search-hotel --dest-name "{town}" --hotel-types "客栈" --key-words "四合院" --sort rate_desc

Output: Traditional courtyard inns.

Playbook C: Budget Inn

Trigger: "cheap inn", "便宜客栈"

flyai search-hotel --dest-name "{town}" --hotel-types "客栈" --sort price_asc

Output: Affordable ancient town accommodation.

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 "Jiaxing" --keyword "Wuzhen"
flyai search-hotel --dest-name "Wuzhen" --hotel-types "客栈" --sort rate_desc

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 detailUrl.
  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 ancient towns for inn stays: Wuzhen, Xitang, Zhouzhuang (water towns), Lijiang, Dali, Fenghuang (ethnic towns), Pingyao, Hongcun (historical towns). Stay inside the scenic area for best experience — some towns charge entry fees, staying inside gives free access. Book directly with inn for better rates.

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