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Beachfront Resort Finder

通过 flyai CLI 检索海滨/海岛度假酒店与沙滩海岛景点,支持海景房、私人海滩、低价等场景,可按评分或价格排序,输出含预订链接的对比表格;数据须来自实时命令结果,需先安装并运行 flyai 命令。

xiejinsong
xiejinsong
热度 33.97
最近更新 2026-05-11 17:41:50
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 beachfront-resort-finder
Metadata
name
beachfront-resort-finder
description
Find beach and island resorts — oceanfront rooms, private beaches, tropical paradise stays with direct beach access and water activities. 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
1.0.0
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: beachfront-resort-finder

Overview

Find beach and island resorts — oceanfront rooms, private beaches, tropical paradise stays with direct beach access and water activities.

When to Activate

User query contains:

  • English: "beach resort", "oceanfront", "seaside", "island resort"
  • Chinese: "海边度假村", "海景房", "海滩酒店", "海岛住宿"

Do NOT activate for: beach attraction → beach-island-guide

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: Beach Resort

Trigger: "beach hotel", "海边酒店"

flyai search-poi --city-name "{city}" --category "沙滩海岛"
flyai search-hotels --dest-name "{city}" --key-words "海景" --sort rate_desc --check-in-date {in} --check-out-date {out}

Output: Beach POIs → oceanfront hotels.

Playbook B: Private Beach

Trigger: "private beach resort"

flyai search-hotels --dest-name "{city}" --key-words "私人海滩" --sort rate_desc --check-in-date {in} --check-out-date {out}

Output: Resorts with private beach access.

Playbook C: Budget Beach

Trigger: "cheap beach hotel"

flyai search-hotels --dest-name "{city}" --key-words "海景" --sort price_asc --check-in-date {in} --check-out-date {out}

Output: Affordable oceanfront options.

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 "Sanya" --category "沙滩海岛"
flyai search-hotels --dest-name "Sanya" --key-words "海景" --sort rate_desc --check-in-date 2026-01-15 --check-out-date 2026-01-18

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.

China beach destinations: Sanya (Yalong Bay, Haitang Bay), Xiamen, Beihai, Wanning. International: Bali, Phuket, Maldives, Boracay. Sea-view rooms cost 30-80% more than garden-view. Best beach season varies: Sanya year-round, SE Asia Nov-Apr (dry season).

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