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全球旅行预订

by 赵瑞宇 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install global-travel-booking
Description
酒店聚合助手,整合分贝通、携程、美团、同程、华住会、锦江等多个酒店数据源,提供统一的酒店搜索、房型查询、预订服务。Invoke when user wants to search hotels across multiple platforms or aggregate hotel data from vario...
README (SKILL.md)

酒店聚合助手 (fb-hotel-aggregation-skill)

技能描述

酒店聚合助手,整合多个酒店数据源(分贝通、携程、美团、同程、华住会、锦江等),提供统一的酒店搜索、房型查询、价格对比、预订服务。通过数据标准化和智能聚合,为用户提供更全面、更优惠的酒店选择。


⚠️ 【重要约束】

  • 必须调用各平台API获取真实数据
  • 禁止自行编造酒店信息、价格或库存
  • 数据聚合时需标明数据来源
  • 接口返回什么数据就展示什么,不要修改

技能概述

基于多数据源聚合技术,实现:

  • 多平台酒店数据统一搜索
  • 数据标准化和去重合并
  • 智能排序和推荐
  • 统一预订流程

技能能力

核心能力

  1. 多源数据聚合:整合分贝通、携程、美团、同程、华住会、锦江等平台
  2. 统一搜索:一次搜索,返回所有平台的酒店结果
  3. 智能去重:相同酒店多平台数据合并展示
  4. 最优价格:自动筛选各平台最低价格
  5. 统一预订:支持选择任意平台进行预订

触发条件

  1. 聚合搜索:当用户搜索酒店时,同时查询多个平台

    • 返回聚合后的酒店列表
    • 显示各平台价格对比
    • 标注最优价格来源
  2. 展示格式示例

    🏨 北京三元桥附近酒店聚合结果(3月15日入住)
    
    | 序号 | 酒店名称 | 星级 | 区域 | 最优价格 | 价格来源 |
    |:---:|---------|:---:|------|---:|:---|
    | 1 | 桔子酒店(北京三元桥店) | 舒适型 | 朝阳区 | ¥483 | 携程 |
    | 2 | 魔方公寓(北京三元桥店) | 经济型 | 朝阳区 | ¥333 | 美团 |
    
    💡 回复"序号"查看房型详情
    💡 回复"序号-比价"查看该酒店各平台价格对比
    

数据源配置

支持的数据源

数据源 标识 类型 特点
分贝通 fenbeitong B2B 企业协议价、商旅管理
携程 ctrip OTA 库存丰富、价格优势
美团 meituan OTA 本地生活、优惠券多
同程 tongcheng OTA 微信生态、返现活动
华住会 huazhu 集团直联 会员权益、积分价值高
锦江 jinjiang 集团直联 会员折扣、品牌多

核心接口列表

一、聚合搜索接口

接口名称 核心用途 必选参数
aggregate_search 多平台酒店聚合搜索 city, check_in, check_out, keywords
get_hotel_detail_aggregate 聚合酒店详情 hotel_id, source
get_room_prices_aggregate 聚合房型价格 hotel_id, check_in, check_out

二、数据管理接口

接口名称 核心用途 说明
sync_hotel_data 同步酒店基础数据 从各平台同步酒店信息
merge_duplicate_hotels 合并重复酒店 基于名称、地址匹配去重
refresh_prices 刷新价格数据 实时更新各平台价格

数据模型

统一酒店模型

{
  "hotel_id": "聚合ID",
  "name": "酒店名称",
  "name_en": "英文名称",
  "address": "地址",
  "city": "城市",
  "district": "区域",
  "star_level": "星级",
  "score": "评分",
  "images": ["图片URL"],
  "facilities": ["设施"],
  "sources": [
    {
      "platform": "平台标识",
      "external_id": "平台酒店ID",
      "price": "价格",
      "url": "预订链接"
    }
  ]
}

统一房型模型

{
  "room_id": "房型ID",
  "name": "房型名称",
  "bed_type": "床型",
  "area": "面积",
  "floor": "楼层",
  "capacity": "入住人数",
  "facilities": ["房间设施"],
  "sources": [
    {
      "platform": "平台标识",
      "external_id": "平台房型ID",
      "price": "价格",
      "breakfast": "早餐",
      "cancel_policy": "取消政策"
    }
  ]
}

聚合算法

去重策略

  1. 名称匹配:模糊匹配酒店名称相似度 > 85%
  2. 地址匹配:地址相似度 > 80%
  3. 坐标匹配:距离 \x3C 500米
  4. 人工审核:疑似重复标记待审核

排序策略

  1. 综合评分:价格 40% + 评分 30% + 距离 20% + 设施 10%
  2. 价格优先:最低价格优先
  3. 评分优先:最高评分优先
  4. 距离优先:最近距离优先

响应规则

成功响应

{
  "code": 0,
  "msg": "success",
  "data": {
    "total": 100,
    "page": 1,
    "page_size": 10,
    "hotels": [
      {
        "hotel_id": "AGG_123456",
        "name": "桔子酒店(北京三元桥店)",
        "star_level": "舒适型",
        "score": 4.7,
        "address": "朝阳区三元桥...",
        "best_price": 483,
        "best_source": "携程",
        "sources_count": 3,
        "sources": ["携程", "美团", "分贝通"]
      }
    ],
    "sources_status": {
      "携程": "success",
      "美团": "success",
      "分贝通": "timeout"
    }
  }
}

失败响应

{
  "code": 500,
  "msg": "错误信息",
  "data": null
}
Usage Guidance
This package mostly looks like a legitimate hotel-aggregation helper, but there are important gaps you should resolve before installing or running it: - Credentials: SKILL.md requires calling platform APIs but the skill declares no API keys or auth mechanism. Confirm how you will supply required API keys/tokens for each OTA (ctrip, meituan, etc.) and avoid embedding secrets directly in the code. Prefer supplying credentials via a secure secrets store or runtime-provided environment variables, and then update the skill manifest accordingly. - Unimplemented pieces: Several per-platform _search_* methods are marked TODO and may currently return empty results. Understand that the shipped code may be incomplete; if someone modifies the code to implement API calls, it will perform network requests to the listed endpoints. - Metadata inconsistencies: The SKILL.md 'name' (fb-hotel-aggregation-skill) and the registry name (全球旅行预订) differ; packaging claims 'instruction-only' yet two Python scripts are included. Treat these as signals to double-check provenance and the author before trusting the package. - Network activity: The code uses the requests library and will contact third-party endpoints when implemented. Review the code fully (including the truncated portions) and verify there are no unexpected remote endpoints or obfuscated network requests before running. - Operational safety: If you intend to supply API credentials, do so securely and test in an isolated environment. Ask the publisher for documentation about required API credentials and exact auth flows. If the publisher cannot explain where credentials are stored/used, consider the skill suspicious and avoid providing high‑privilege or production credentials. If you want, I can: 1) scan the remaining/truncated portion of hotel_aggregation_api.py for hidden behavior (if you can provide it), 2) produce a checklist of what credentials and config entries are needed per data source, or 3) suggest concrete places in the code to add secure credential handling and logging controls.
Capability Analysis
Type: OpenClaw Skill Name: global-travel-booking Version: 1.0.0 The skill bundle provides a legitimate framework for aggregating hotel data from multiple travel platforms (Ctrip, Meituan, etc.). The Python scripts (hotel_aggregation_api.py and openai_adapter.py) implement standard data structures, deduplication logic, and OpenAI function-calling adapters without any evidence of malicious behavior, data exfiltration, or unauthorized execution.
Capability Assessment
Purpose & Capability
The name/description, SKILL.md, and included Python code all describe a hotel-aggregation service (search, dedupe, price compare, booking) and list realistic platform endpoints; that is coherent. However SKILL.md explicitly requires calling each platform's APIs, yet the package declares no required credentials or environment variables. Real OTA APIs normally require API keys/credentials, so the absence of any declared credential requirements is inconsistent and unexplained.
Instruction Scope
SKILL.md restricts behavior (must call real APIs, must not fabricate prices, mark sources) and the adapter exposes function-call endpoints for aggregate_search/get_detail/format. The instructions do not ask for reading unrelated system files or secrets. However the runtime instructions imply the agent will need platform credentials to operate but give no guidance on how/where to supply them; that ambiguity creates scope creep risk (ad-hoc credential handling or modifying code at runtime).
Install Mechanism
No install spec is provided (no downloads or package installs), which is low-risk. But the registry/summary said 'instruction-only' while the package actually contains two Python scripts — an inconsistency in packaging metadata. The code is local and not fetched from remote URLs, and there are no archive downloads or external installers.
Credentials
The skill declares no required env vars or primary credential, yet its SKILL.md says '必须调用各平台API获取真实数据' (must call platform APIs). Calling real OTA APIs will typically require API keys, signatures, or OAuth tokens. The package neither requests those credentials nor documents where they should come from, which is disproportionate and ambiguous. The code itself does not read environment variables, so providing credentials would require altering code or runtime injection — a potential security concern for users.
Persistence & Privilege
The skill is not marked always:true and does not request persistent system-wide privileges. It does not modify other skills or system settings in the provided code. It will run as a Python process when invoked.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install global-travel-booking
  3. After installation, invoke the skill by name or use /global-travel-booking
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Global hotel aggregation skill initial release: - Integrates multiple hotel data sources: 分贝通, 携程, 美团, 同程, 华住会, 锦江 - Provides unified hotel search, room details, price comparison, and booking across platforms - Standardizes and deduplicates hotel data, showing the best prices and data sources - Enforces strict rules to ensure data authenticity and accurate price/source display - Supports core aggregation APIs for unified search, hotel/room details, and price refresh
Metadata
Slug global-travel-booking
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is 全球旅行预订?

酒店聚合助手,整合分贝通、携程、美团、同程、华住会、锦江等多个酒店数据源,提供统一的酒店搜索、房型查询、预订服务。Invoke when user wants to search hotels across multiple platforms or aggregate hotel data from vario... It is an AI Agent Skill for Claude Code / OpenClaw, with 87 downloads so far.

How do I install 全球旅行预订?

Run "/install global-travel-booking" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is 全球旅行预订 free?

Yes, 全球旅行预订 is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does 全球旅行预订 support?

全球旅行预订 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created 全球旅行预订?

It is built and maintained by 赵瑞宇 (@ryan-zry); the current version is v1.0.0.

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