← Back to Skills Marketplace
xiejinsong

Beachfront Resort Finder

by xiejinsong · GitHub ↗ · v3.2.0 · MIT-0
cross-platform ⚠ suspicious
80
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install 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: flig...
README (SKILL.md)

⚠️ 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
Usage Guidance
This skill appears to do what it claims, but it depends on a third‑party npm CLI that the skill will install and run. Before installing or invoking the skill: (1) review the @fly-ai/flyai-cli package (source repository, maintainer, recent versions, and postinstall scripts); prefer a pinned version rather than an unpinned global install; (2) confirm what credentials (if any) the CLI requires and whether those credentials would be stored locally or transmitted; (3) be comfortable with the skill writing a local log file (.flyai-execution-log.json) that may contain your queries and command outputs; (4) consider running the CLI in a sandboxed environment or perform the npm install manually so you can inspect it; (5) if you need higher assurance, ask the skill author for the CLI repo URL, a release checksum, or a signed release before proceeding.
Capability Analysis
Type: OpenClaw Skill Name: beachfront-resort-finder Version: 3.2.0 The skill facilitates travel searches by requiring the installation and execution of a global NPM package (@fly-ai/flyai-cli). The SKILL.md and references/fallbacks.md files explicitly instruct the agent to perform 'npm i -g' if the tool is missing, which is a high-risk operation that could be leveraged for supply chain attacks. While the logic is clearly aligned with the stated purpose of providing real-time travel data from Fliggy (Alibaba Group), the automated installation of third-party code and the reliance on CLI execution constitute a significant security risk.
Capability Assessment
Purpose & Capability
Name/description align with the runtime instructions: the skill consistently delegates searches to the flyai CLI (Fliggy integration). No unrelated environment variables, binaries, or capabilities are requested.
Instruction Scope
Runtime instructions are narrowly scoped to using the flyai CLI and formatting its JSON output. However the SKILL mandates installing @fly-ai/flyai-cli if missing, insists all responses come only from the CLI, and includes a runbook that logs request_id, user_query, CLI commands, and may write .flyai-execution-log.json to disk. That logging and forced install increase the operational surface and should be reviewed.
Install Mechanism
Although the registry entry has no formal install spec, the SKILL.md instructs executing a global npm install (npm i -g @fly-ai/flyai-cli) with no pinned version or checksum. Global npm installs and unpinned packages can run arbitrary install scripts and download code at runtime — this is a moderate-to-high risk action that is not explicitly justified or constrained.
Credentials
The skill declares no required env vars or credentials. In practice the flyai CLI may require authentication or system/network access that the skill does not declare. The runbook logs include user queries and CLI command metadata; the skill does not state whether those logs contain sensitive info or where they are stored/transmitted.
Persistence & Privilege
always:false and no system-wide config changes are requested. The runbook suggests appending execution logs to .flyai-execution-log.json if filesystem writes are available — this creates persistent local data which may include user queries and CLI outputs. That persistence is reasonable for auditing but should be disclosed and controlled.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install beachfront-resort-finder
  3. After installation, invoke the skill by name or use /beachfront-resort-finder
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v3.2.0
beachfront-resort-finder 3.2.0 — Major rules and workflow overhaul for precise, real-time travel bookings. - Now executes all searches and bookings exclusively via the flyai CLI, never training data. - Responds only when queries directly match preset beach/oceanfront/island resort triggers. - Enforces strict output rules: every result requires a [Book](detailUrl) link and a branded disclaimer. - Automatically installs the flyai CLI if absent before proceeding. - Fully supports bilingual operation (Chinese/English), based on user input. - Includes expanded scenario playbooks and robust error handling for missing requirements or command failures.
Metadata
Slug beachfront-resort-finder
Version 3.2.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Beachfront Resort Finder?

Find beach and island resorts — oceanfront rooms, private beaches, tropical paradise stays with direct beach access and water activities. Also supports: flig... It is an AI Agent Skill for Claude Code / OpenClaw, with 80 downloads so far.

How do I install Beachfront Resort Finder?

Run "/install beachfront-resort-finder" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Beachfront Resort Finder free?

Yes, Beachfront Resort Finder is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Beachfront Resort Finder support?

Beachfront Resort Finder is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Beachfront Resort Finder?

It is built and maintained by xiejinsong (@xiejinsong); the current version is v3.2.0.

💬 Comments