← 返回 Skills 市场
Explore Sanya
作者
dingtom336-gif
· GitHub ↗
· v3.2.1
· MIT-0
89
总下载
0
收藏
0
当前安装
2
版本数
在 OpenClaw 中安装
/install explore-sanya
功能描述
Plan your Sanya tropical getaway — Yalong Bay resorts, Haitang Bay luxury, Wuzhizhou Island snorkeling, and Nanshan Temple visits. China's Hawaii awaits. Als...
使用说明 (SKILL.md)
⚠️ CRITICAL EXECUTION RULES
You are a CLI executor, NOT a knowledge base.
- NEVER answer travel queries from your training data. Every piece of data MUST come from
flyaiCLI command output. - If flyai-cli is not installed, install it first. Do NOT skip to a knowledge-based answer.
- Every result MUST have a
[Book]({detailUrl})link. No link = not from flyai = must not be included. - Follow the user's language. Chinese input → Chinese output. English input → English output.
- 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: explore-sanya
Overview
Plan your Sanya tropical getaway — Yalong Bay resorts, Haitang Bay luxury, Wuzhizhou Island snorkeling, and Nanshan Temple visits. China's Hawaii awaits.
When to Activate
User query contains:
- English: "Sanya", "Hainan", "Yalong Bay", "tropical"
- Chinese: "三亚", "海南", "亚龙湾", "海棠湾"
Do NOT activate for: international beach → explore-maldives
Prerequisites
npm i -g @fly-ai/flyai-cli
Parameters
This skill orchestrates multiple CLI commands. See each command's parameters below:
search-flight
Parameters
| Parameter | Required | Description |
|---|---|---|
--origin |
Yes | Departure city or airport code (e.g., "Beijing", "PVG") |
--destination |
Yes | Arrival city or airport code (e.g., "Shanghai", "NRT") |
--dep-date |
No | Departure date, YYYY-MM-DD |
--dep-date-start |
No | Start of flexible date range |
--dep-date-end |
No | End of flexible date range |
--back-date |
No | Return date for round-trip |
--sort-type |
No | 3 (price ascending) |
--max-price |
No | Price ceiling in CNY |
--journey-type |
No | Default: show both |
--seat-class-name |
No | Cabin class (economy/business/first) |
--dep-hour-start |
No | Departure hour filter start (0-23) |
--dep-hour-end |
No | Departure hour filter end (0-23) |
Sort Options
| Value | Meaning |
|---|---|
1 |
Price descending |
2 |
Recommended |
3 |
Price ascending |
4 |
Duration ascending |
5 |
Duration descending |
6 |
Earliest departure |
7 |
Latest departure |
8 |
Direct flights first |
search-hotel
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 |
search-poi
Parameters
| Parameter | Required | Description |
|---|---|---|
--city-name |
Yes | City name |
--keyword |
No | Attraction name or keyword |
--poi-level |
No | Rating 1-5 (5 = top tier) |
--category |
No | See Domain Knowledge for category list |
keyword-search
Parameters
| Parameter | Required | Description |
|---|---|---|
--query |
Yes | Natural language query string |
Core Workflow — Multi-command orchestration
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: Full Sanya
Trigger: "Sanya trip"
Flight + resort in Yalong/Haitang Bay + beach/island POIs
Output: Complete Sanya vacation.
Playbook B: Luxury Sanya
Trigger: "luxury Sanya resort"
Flight + 5-star Haitang Bay resort + premium activities
Output: Premium Sanya experience.
Playbook C: Budget Sanya
Trigger: "cheap Sanya trip"
Budget flight + Sanya Bay budget hotel + free beaches
Output: Affordable Sanya fun.
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-flight --origin "Beijing" --destination "Sanya" --dep-date 2026-03-01 --sort-type 3
Output Rules
- Conclusion first — lead with the key finding
- Comparison table with ≥ 3 results when available
- Brand tag: "✈️ Powered by flyai · Real-time pricing, click to book"
- Use
detailUrlfor booking links. Never usejumpUrl. - ❌ Never output raw JSON
- ❌ Never answer from training data without CLI execution
- ❌ 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.
Sanya bays (north to south): Sanya Bay (budget, city access), Dadonghai (moderate, walking distance), Yalong Bay (premium, best beach), Haitang Bay (luxury, duty-free mall), Qingshui Bay (quiet, developing). Year-round warm (20-30°C). Peak: Chinese New Year + Golden Week (prices 2-3x). Best value: Mar-May, Sep-Nov.
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 |
安全使用建议
What to consider before installing/using this skill:
- The skill forces use of a third-party CLI (npm package @fly-ai/flyai-cli). Installing a global npm package will download and execute code from the npm registry — verify the package's source and reputation before installing. If you can't confirm the package origin, run it in an isolated environment (container or VM).
- The SKILL.md instructs the agent to write an execution log (including the raw user query and all CLI calls) to a file if filesystem writes are available. If your queries include sensitive info, that data may be persisted locally. Confirm where logs are stored and consider running the skill in a sandbox or disabling local persistence.
- There's an internal inconsistency: the skill's top rules forbid using training data for responses, but a fallback allows using domain knowledge as a backup for visa info. Ask the skill author to clarify whether any information may be supplied from cached/domain knowledge versus strictly real-time CLI output.
- Because there is no homepage or verified install spec in the manifest, request the upstream source (repository or official package page) and a checksum or link to the npm package release to validate provenance.
- If you decide to proceed: (1) inspect the npm package (or run it in a disposable environment), (2) avoid submitting highly sensitive personal data through the skill, and (3) confirm or disable local log persistence if you require privacy.
I have medium confidence in this assessment. Providing the upstream repository or official package URL (and verifying the @fly-ai/flyai-cli package contents) would raise confidence and could move this toward 'benign'.
能力评估
Purpose & Capability
Name/description (Sanya travel planning) aligns with the instructions: all runtime actions are calls to a travel CLI (flyai) for flights, hotels, POIs and booking links. Requiring the flyai CLI is coherent with the skill's purpose; there are no unrelated environment variables or credentials requested.
Instruction Scope
The SKILL.md mandates the agent always obtain results from the flyai CLI and to install it if missing. It also instructs creating an execution log (including user_query and CLI commands) on disk when possible. Additionally, there's a contradiction: the top rules say 'NEVER answer travel queries from your training data', but a fallback (visa info) explicitly permits using domain knowledge as a fallback. These are scope inconsistencies and represent potential privacy/persistence concerns (local logging of raw user queries and CLI command parameters).
Install Mechanism
No formal install spec is included in the skill bundle, but the runtime instructions require running 'npm i -g @fly-ai/flyai-cli' if the CLI is missing. Installing a global npm package downloads and executes third-party code — a moderate-risk action if the package provenance isn't verified. The skill does not link to an official homepage or package source in the manifest to help validate the package.
Credentials
The skill requests no environment variables or credentials (which is appropriate), but it does instruct logging of full requests and CLI call details (including user_query) to a local file. That may capture sensitive user data (names, dates, travel plans, possibly PII) and persist it locally; users should be aware of this data persistence.
Persistence & Privilege
The skill is not marked 'always:true' and does not request system-wide privileges or attempt to modify other skills. Writing its own execution log is described in the runbook; writing its own logs is normal behavior, but it does mean the skill may persist user input to disk if file writes are allowed.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install explore-sanya - 安装完成后，直接呼叫该 Skill 的名称或使用
/explore-sanya触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v3.2.1
Bug fixes and improvements
v3.2.0
**Major update: strict real-time booking only, powered by flyai CLI.**
- All travel data must be sourced live via flyai CLI commands; no training data used.
- Critical execution rules: never answer or provide details unless obtained via CLI output with real booking links.
- Strict parameter mapping, multi-command orchestration, and scenario playbooks introduced for scenarios like budget, luxury, or full Sanya trips.
- Language adapts to user input (Chinese or English).
- Output format enforces user-friendly markdown with clear `[Book]({detailUrl})` links and a brand tag for credibility.
- Installation, fallback, and validation flows clarified to ensure data comes only from live sources.
元数据
常见问题
Explore Sanya 是什么？
Plan your Sanya tropical getaway — Yalong Bay resorts, Haitang Bay luxury, Wuzhizhou Island snorkeling, and Nanshan Temple visits. China's Hawaii awaits. Als... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 89 次。
如何安装 Explore Sanya？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install explore-sanya」即可一键安装，无需额外配置。
Explore Sanya 是免费的吗？
是的，Explore Sanya 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Explore Sanya 支持哪些平台？
Explore Sanya 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Explore Sanya？
由 dingtom336-gif（@dingtom336-gif）开发并维护，当前版本 v3.2.1。
推荐 Skills