Skill flagged — suspicious patterns detected

ClawHub Security flagged this skill as suspicious. Review the scan results before using.

Transit Risk Assessment & Delay Hotel Recommendations & Last-Mile Transport Check

v1.0.2

旅行交通风险检查助手,提供转机风险评估、延误酒店推荐、最后一公里交通检查三大核心功能

0· 92·0 current·0 all-time

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for mlyjqx/travel-risk-checker.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Transit Risk Assessment & Delay Hotel Recommendations & Last-Mile Transport Check" (mlyjqx/travel-risk-checker) from ClawHub.
Skill page: https://clawhub.ai/mlyjqx/travel-risk-checker
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install travel-risk-checker

ClawHub CLI

Package manager switcher

npx clawhub@latest install travel-risk-checker
Security Scan
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Suspicious
high confidence
!
Purpose & Capability
The skill's name, description, and SKILL.md all align on transit risk, delay-hotel recommendations, and last-mile checks. However, the SKILL.md requires integration with three MCP servers (travel-data, hotel-booking, city-transport) and their API keys (TRAVEL_API_KEY, HOTEL_API_KEY, TRANSPORT_API_KEY) even though the registry metadata lists no required environment variables or primary credential. That undeclared credential requirement is inconsistent with the published skill metadata.
!
Instruction Scope
Runtime instructions reference $ARGUMENTS, $ORDER_DATA, $USER_LOCATION and call specific MCP methods (e.g., travel-data.get_order, hotel-booking.search_hotels). They also describe push notifications, SMS/email delivery, and automatic triggers. Those output channels and the data access (order data, flight status, user location) imply access to sensitive user data and communication channels, but the skill does not declare the credentials or permissions needed for those actions. The instructions also tell the agent to run npx commands to launch MCP servers at runtime, which will download and execute remote packages.
!
Install Mechanism
There is no formal install spec, but the SKILL.md requires launching MCP servers via npx (npx -y @travel/mcp-server, etc.). That means code will be pulled from npm (or the package's configured registry) at runtime and executed. Runtime npx installs are a moderate-to-high risk because arbitrary code is fetched and executed without an explicit install policy or pinned, audited artifact. package.json includes publishConfig that points to an internal registry (https://contextlab.alibaba-inc.com/skill), which raises additional questions about package provenance.
!
Credentials
The SKILL.md references TRAVEL_API_KEY, HOTEL_API_KEY, and TRANSPORT_API_KEY as environment variables for MCP servers, but the skill metadata declares no required env vars. Other necessary credentials for push notifications, SMS/email gateways, or accessing user orders are not declared either. Requesting multiple external API keys is reasonable for this functionality, but the absence of declared env vars and no explanation of required key scopes or minimal privileges is a mismatch and a potential risk for accidental over-permissioning or secret leakage.
Persistence & Privilege
always:false and disable-model-invocation:false (default) — the skill is not force-included and can be invoked autonomously like normal skills. The skill does not declare actions that modify other skills or global agent configuration. No install-time persistence is declared. Still, runtime npx execution could introduce code that persists or exfiltrates data if the fetched packages are malicious; that risk ties back to the install_mechanism concern above.
What to consider before installing
This skill's functionality (transfer risk, hotel recommendations, last-mile checks) is coherent, but there are important mismatches and runtime risks you should resolve before installing: 1) Confirm exactly which environment variables and API keys are required (SKILL.md references TRAVEL_API_KEY, HOTEL_API_KEY, TRANSPORT_API_KEY) and ensure they are declared and limited in scope. 2) Ask the publisher for the source, checksum, and trust model for the MCP packages (@travel/mcp-server, @hotel/mcp-server, @city-transport/mcp-server). Running npx at runtime will fetch and execute remote code—only allow this if the packages are audited/trusted. 3) Verify where push notifications, SMS/email, and order data access will be sent/received and what credentials those integrations require; avoid providing high-privilege keys (e.g., broad cloud admin keys). 4) If you must test, run the skill in a restricted sandbox with network and secret access limited, monitor outbound network calls, and avoid reusing production credentials. 5) Prefer a version-pinned, audited install artifact or a manifest that explicitly lists required env vars/permissions; if the publisher cannot provide that, treat the skill as higher-risk and consider not installing.

Like a lobster shell, security has layers — review code before you run it.

latestvk972t5fx353eh1cw70mf6bsk2x841tvw
92downloads
0stars
3versions
Updated 3w ago
v1.0.2
MIT-0

参数获取

获取以下参数:

  • $ARGUMENTS: 用户原始输入
  • $ORDER_DATA: 交通订单数据(如有)
  • $USER_LOCATION: 用户当前位置(如有)

核心功能

基于用户输入或订单数据,提供以下三大核心服务:

1. 极限转机风险检查

触发条件: 用户输入航班信息或检测到联程航班订单

检查内容:

  • 转机时间是否充足
  • 是否需要重新托运行李
  • 是否需要入境再出境
  • 是否需要更换航站楼
  • 机场平均转机耗时
  • 赶不上概率评估

输出格式:

【转机风险评估】
转机机场:{机场名称}
航站楼:{T1 → T2}
转机时间:{用户时间}
平均耗时:{机场平均时间}
风险项:
  - 需重新安检 ✓
  - 需入境再出境 ✓
  - 航站楼不同 ✓
错过概率:{XX}%
建议:{改签/提前到达/快速通道}

示例:

【转机风险评估】
转机机场:香港国际机场 (HKG)
航站楼:T1 → T1
转机时间:1 小时 10 分钟
平均耗时:65 分钟
风险项:
  - 需重新安检 ✓
  - 需入境再出境 ✗
  - 航站楼不同 ✗
错过概率:35%
建议:建议改签至 2 小时以上转机时间,或购买快速安检服务

2. 航班延误酒店保命助手

触发条件: 检测到航班延误 > 2 小时 或 航班取消

检查内容:

  • 预计到达时间
  • 到达地酒店入住政策
  • 24 小时前台酒店
  • 机场附近酒店(15 分钟车程内)
  • 凌晨 check-in 支持

输出格式:

【延误酒店推荐】
到达时间:{凌晨 HH:MM}
城市:{城市名称}
机场:{机场名称}

可入住酒店:
1. {酒店 A}
   - 距离:{X.X km / X 分钟车程}
   - 前台:24 小时
   - 服务:{机场接送/免费 shuttle}
   - 价格:{¥XXX 起}

2. {酒店 B}
   - 距离:{X.X km / X 分钟车程}
   - 前台:24 小时
   - 服务:{机场接送}
   - 价格:{¥XXX 起}

建议:立即预订,避免深夜无房

示例:

【延误酒店推荐】
到达时间:凌晨 1:40
城市:上海
机场:浦东国际机场 (PVG)

可入住酒店:
1. 机场大酒店
   - 距离:2.3 km / 5 分钟车程
   - 前台:24 小时
   - 服务:免费机场接送
   - 价格:¥458 起

2. 浦东机场宾馆
   - 距离:1.8 km / 4 分钟车程
   - 前台:24 小时
   - 服务:航站楼直达
   - 价格:¥528 起

建议:立即预订,避免深夜无房

3. 最后一公里交通失效提醒

触发条件: 检测到晚间到达交通订单(航班/高铁 22:00 后到达)

检查内容:

  • 目的地城市地铁末班车时间
  • 机场大巴运营时间
  • 夜班公交路线
  • 打车排队情况
  • 替代交通方案

输出格式:

【交通失效预警】
到达时间:{HH:MM}
到达站点:{站点名称}
城市:{城市名称}

交通状态:
  - 地铁:{已停运/末班车 XX:XX}
  - 机场大巴:{已停运/末班车 XX:XX}
  - 夜班公交:{有/无}
  - 打车排队:{约 X 分钟}

建议:
  - 改为{推荐时间}前到达的车次
  - 或预订接站车(¥XXX 起)
  - 或提前预约网约车

示例:

【交通失效预警】
到达时间:23:10
到达站点:西安北站
城市:西安

交通状态:
  - 地铁:已停运(末班车 23:00)
  - 机场大巴:已停运(末班车 22:30)
  - 夜班公交:无
  - 打车排队:约 60 分钟

建议:
  - 改为 22:00 前到达的车次
  - 或预订接站车(¥120 起)
  - 或提前预约网约车

MCP 集成

MCP Server 配置

所需 MCP Servers:

mcpServers:
  travel-data:
    command: npx
    args: ["-y", "@travel/mcp-server"]
    env:
      TRAVEL_API_KEY: "${TRAVEL_API_KEY}"
  
  hotel-booking:
    command: npx
    args: ["-y", "@hotel/mcp-server"]
    env:
      HOTEL_API_KEY: "${HOTEL_API_KEY}"
  
  city-transport:
    command: npx
    args: ["-y", "@city-transport/mcp-server"]
    env:
      TRANSPORT_API_KEY: "${TRANSPORT_API_KEY}"

MCP 工具定义

工具 1:flight_transit_risk_check

用途: 检查航班转机风险

参数:

{
  "type": "object",
  "properties": {
    "flight_no_1": {"type": "string", "description": "第一程航班号"},
    "flight_no_2": {"type": "string", "description": "第二程航班号"},
    "transit_airport": {"type": "string", "description": "转机机场代码"},
    "transit_time_minutes": {"type": "integer", "description": "转机时间(分钟)"},
    "terminal_1": {"type": "string", "description": "第一程航站楼"},
    "terminal_2": {"type": "string", "description": "第二程航站楼"}
  },
  "required": ["flight_no_1", "flight_no_2", "transit_airport", "transit_time_minutes"]
}

返回示例:

{
  "risk_level": "HIGH",
  "transit_airport": "HKG",
  "terminals": "T1 → T1",
  "avg_transit_time": 65,
  "user_time": 70,
  "miss_probability": 0.35,
  "risk_items": ["security_recheck", "immigration_required"],
  "suggestions": ["建议改签至 2 小时以上转机时间", "购买快速安检服务"]
}

工具 2:delay_hotel_recommend

用途: 推荐延误时可入住的酒店

参数:

{
  "type": "object",
  "properties": {
    "airport_code": {"type": "string", "description": "机场代码"},
    "arrival_time": {"type": "string", "description": "预计到达时间 (ISO 8601)"},
    "max_distance_km": {"type": "number", "description": "最大距离(公里)", "default": 10},
    "require_24h_reception": {"type": "boolean", "description": "是否要求 24 小时前台", "default": true},
    "require_airport_shuttle": {"type": "boolean", "description": "是否要求机场接送", "default": true}
  },
  "required": ["airport_code", "arrival_time"]
}

返回示例:

{
  "hotels": [
    {
      "name": "机场大酒店",
      "distance_km": 2.3,
      "drive_time_minutes": 5,
      "reception_24h": true,
      "airport_shuttle": true,
      "price_from": 458,
      "available_rooms": 3
    }
  ]
}

工具 3:last_mile_transport_check

用途: 检查最后一公里交通可用性

参数:

{
  "type": "object",
  "properties": {
    "station_name": {"type": "string", "description": "到达站点名称"},
    "station_type": {"type": "string", "enum": ["airport", "train_station"], "description": "站点类型"},
    "arrival_time": {"type": "string", "description": "预计到达时间 (ISO 8601)"},
    "city_code": {"type": "string", "description": "城市代码"}
  },
  "required": ["station_name", "station_type", "arrival_time", "city_code"]
}

返回示例:

{
  "metro_status": "CLOSED",
  "metro_last_train": "23:00",
  "airport_bus_status": "CLOSED",
  "airport_bus_last": "22:30",
  "night_bus_available": false,
  "taxi_queue_time": 60,
  "alternatives": [
    {"type": "prebook_car", "price_from": 120},
    {"type": "ride_hailing", "estimated_time": 15}
  ]
}

数据源接入

必须结合以下数据:

数据类型用途触发条件MCP 工具
交通订单获取航班/车次信息用户授权访问订单travel-data.get_order
目的地城市查询当地交通政策订单中包含目的地city-transport.get_city_info
到达时间判断是否深夜到达订单中包含时间travel-data.get_order
实时延误检测航班延误状态航班起飞前 2 小时travel-data.get_flight_status
酒店数据推荐可入住酒店延误 > 2 小时hotel-booking.search_hotels
交通时刻表检查末班车时间到达时间 > 22:00city-transport.get_schedule

自动触发规则

规则 1:转机风险检查

IF 订单类型 == "联程航班"
   AND 转机时间 < 90 分钟
THEN 触发转机风险评估

规则 2:延误酒店推荐

IF 航班状态 == "延误"
   AND 延误时间 > 120 分钟
   AND 到达时间 > 23:00
THEN 触发酒店推荐

规则 3:最后一公里检查

IF 到达时间 > 22:00
   AND 交通方式 IN ["高铁", "飞机"]
THEN 触发交通失效检查

输出渠道

  • 订单详情页:在订单确认前展示风险提示
  • 推送通知:航班延误时主动推送
  • 短信/邮件:深夜到达前发送交通提醒
  • App 首页:行程卡片展示风险状态

风险等级定义

转机风险等级

错过概率计算公式:

miss_probability = base_risk × terminal_factor × immigration_factor × security_factor × time_factor

其中:
- base_risk = 0.1(基础风险)
- terminal_factor = 1.5(同航站楼)或 2.5(不同航站楼)
- immigration_factor = 1.0(无需入境)或 2.0(需入境)
- security_factor = 1.0(无需安检)或 1.5(需安检)
- time_factor = min(2.0, (90 - user_time_minutes) / 30)
等级转机时间错过概率建议
🟢 安全> 120 分钟< 5%正常转机
🟡 注意90-120 分钟5-15%建议快速通道
🟠 风险60-90 分钟15-35%建议改签
🔴 高危< 60 分钟> 35%强烈建议改签

机场平均转机耗时参考数据:

数据来源:IATA Airport Connection Times

国内转国内:45-60 分钟
国内转国际:60-90 分钟
国际转国际:60-75 分钟
国际转国内:75-120 分钟

重点机场参考:
- 香港 (HKG): 65 分钟
- 东京成田 (NRT): 90 分钟
- 首尔仁川 (ICN): 60 分钟
- 新加坡 (SIN): 55 分钟
- 曼谷 (BKK): 75 分钟
- 吉隆坡 (KUL): 70 分钟

深夜到达风险等级

等级到达时间交通状态建议
🟢 安全< 22:00公共交通正常正常出行
🟡 注意22:00-23:00部分交通停运建议预约车
🟠 风险23:00-01:00公共交通停运必须预约车
🔴 高危> 01:00仅出租车可用提前安排住宿

交通可用性判断规则:

IF arrival_time < metro_last_train THEN metro_available = true
ELSE metro_available = false

IF arrival_time < bus_last THEN bus_available = true
ELSE bus_available = false

IF metro_available OR bus_available THEN risk_level = LOW
ELSE IF taxi_queue_time < 30 THEN risk_level = MEDIUM
ELSE risk_level = HIGH

用户体验优化

提示语风格

  • 简洁明了:直接说明问题和解决方案
  • 数据支撑:使用具体数字(时间、概率、距离)
  • 行动导向:提供明确的下一步建议
  • 语气友好:避免制造焦虑,强调"有帮助"

交互设计

  • 风险可视化:使用颜色标识风险等级
  • 一键操作:提供"改签"、"预订酒店"、"预约车"快捷入口
  • 对比展示:显示当前方案 vs 推荐方案
  • 倒计时提醒:关键时间节点前主动提醒

数据更新频率

数据类型更新频率来源缓存策略
航班状态实时(5 分钟)航司 API / 飞常准不缓存,实时查询
地铁时刻每日 00:00城市交通数据缓存 24 小时
酒店房态实时(15 分钟)酒店 API / 携程缓存 15 分钟
打车排队实时(10 分钟)网约车 API缓存 10 分钟
机场转机时间每周IATA / 机场官方缓存 7 天
天气数据每小时气象局 API缓存 1 小时

降级策略:

IF 实时数据不可用 THEN
  使用缓存数据(如果在有效期内)
ELSE IF 缓存数据过期 THEN
  使用历史平均值
  提示用户"数据可能不准确,建议手动确认"
ELSE
  使用默认安全值
  提示用户"暂时无法获取数据,建议预留更多时间"

错误处理

数据不可用时:

抱歉,暂时无法获取{数据名称}
建议您:
1. 联系{相关机构}确认
2. 预留更多缓冲时间
3. 购买可退改签产品

API 调用失败处理:

错误类型处理策略用户提示
超时重试 2 次,使用缓存"数据加载中,显示的是最近的数据"
认证失败告警,使用默认值"部分功能暂时不可用"
数据为空使用历史平均"基于历史数据估算"
服务不可用降级到离线模式"已切换到离线模式,建议手动确认"

降级策略优先级:

1. 实时 API 数据(首选)
2. 缓存数据(15 分钟内)
3. 历史平均值(同时间段)
4. 行业默认值(安全保守估计)
5. 提示用户手动输入

日志记录:

{
  "timestamp": "2026-04-01T12:00:00Z",
  "user_id": "xxx",
  "check_type": "transit_risk",
  "data_source": "realtime",
  "fallback_used": false,
  "response_time_ms": 234,
  "risk_level": "HIGH"
}

隐私保护

  • 订单数据仅用于风险评估
  • 不存储用户行程历史
  • 不向第三方分享位置信息
  • 用户可随时关闭风险检查功能

Comments

Loading comments...