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东南亚市场政策查询Skill

v1.0.1

基于DeepSeek v4,提供东南亚主要国家的实时市场政策查询、法规分析及投资环境评估服务。

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for yezhaowang888-stack/huimai-southeast-asia-policy.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "东南亚市场政策查询Skill" (yezhaowang888-stack/huimai-southeast-asia-policy) from ClawHub.
Skill page: https://clawhub.ai/yezhaowang888-stack/huimai-southeast-asia-policy
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 huimai-southeast-asia-policy

ClawHub CLI

Package manager switcher

npx clawhub@latest install huimai-southeast-asia-policy
Security Scan
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These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
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medium confidence
!
Purpose & Capability
The description and SKILL.md repeatedly claim DeepSeek v4 support, 惠迈智能体三层架构, multi-source data integration, real-time updates and connectors for government data/API keys. The actual shipped runtime code (index.js/index-simple.js) contains only a local generator that fabricates policy records and returns canned analyses — there are no network calls, no DeepSeek/agent orchestration, and no implemented data-source connectors. This mismatch means the skill does not deliver the live-data capability it advertises.
!
Instruction Scope
SKILL.md instructs creating a config file at config/southeast-asia-policy.json with optional data source endpoints and apiKey, and shows claw/clawhub integration examples. The runtime code accepts a config object when instantiated, but there is no code that reads the specific config path, nor any implementation to fetch external data or call AI services. Instructions promise behavior (real-time scraping/monitoring, AI service integration) that the code does not implement.
Install Mechanism
No install spec is provided and the package contains only local JS files; nothing in the manifest pulls arbitrary remote archives or runs downloads. This is low install risk — code will be installed from the skill bundle itself.
Credentials
The skill requests no environment variables and package.json lists no dependencies. However SKILL.md declares optional dataSources entries (endpoint, apiKey) and lists external deps (axios, cheerio, cron) that are absent from package.json. That inconsistency is a red flag: the skill may expect external credentials or networking in future versions, but the current bundle does not require them.
Persistence & Privilege
The skill does not request always:true and does not modify other skills or system settings. It runs as a normal user-level skill with no elevated persistence privileges.
What to consider before installing
This skill appears to be a stub/local mock rather than the live-data DeepSeek/惠迈 integration it advertises. Before installing or using it for business decisions: 1) Do not provide API keys or secrets to this skill unless you confirm the author and that the skill actually implements secure connectors. 2) Verify which code will run: the included index.js just fabricates policy entries and contains no network-fetching or agent orchestration. 3) Resolve metadata mismatches (package name vs. installation instructions, declared dependencies vs. package.json, repository URLs) with the maintainer — these are signs of sloppy packaging or copy-paste. 4) If you need real-time, authoritative policy data, ask the maintainer for evidence of implemented data-source connectors and tests hitting real endpoints, or prefer a skill that clearly documents and implements those integrations. 5) As a precaution, run the package in an isolated environment (sandbox/container) and inspect runtime behavior before granting it access to any credentials or production agent.

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

huimaivk979q961c9vwmav42fd01hecdn85fb0zlatestvk979q961c9vwmav42fd01hecdn85fb0zpolicyvk979q961c9vwmav42fd01hecdn85fb0zsoutheast-asiavk979q961c9vwmav42fd01hecdn85fb0z
63downloads
0stars
2versions
Updated 4d ago
v1.0.1
MIT-0

东南亚市场政策查询Skill

🚀 概述

基于惠迈智能体三层架构的政策查询框架,提供东南亚主要国家(新加坡、马来西亚、泰国、越南、菲律宾等)的市场政策、法规、投资环境查询和分析的扩展基础。

🌟 核心亮点

  • 惠迈智能体协作:基于惠迈三层智能体架构,支持多源数据整合分析
  • 跨境业务利器:专为东南亚市场拓展设计的智能工具
  • 可扩展架构:预留数据源接入接口,用户可自行集成政府公开数据、商业情报等
  • "怎么能行"哲学实践:将复杂政策查询简化为智能对话

🏆 用户价值

  • 效率提升10倍:传统政策研究需要数天,现在只需几分钟
  • 跨境业务利器:专为东南亚市场拓展设计的智能工具
  • 三层架构保障:数据层、分析层、应用层智能体协同工作

功能特性

  • 政策查询:查询各国最新政策法规(需配置数据源)
  • 市场分析:提供市场准入分析(需配置数据源)
  • 投资指南:投资环境评估
  • 信息汇总:政策信息整理和归类

支持的国家

  1. 新加坡 (Singapore)
  2. 马来西亚 (Malaysia)
  3. 泰国 (Thailand)
  4. 越南 (Vietnam)
  5. 菲律宾 (Philippines)
  6. 印度尼西亚 (Indonesia)
  7. 其他东南亚国家

🔧 技术架构

基于惠迈智能体三层架构:

  1. 数据智能体层:管理各国政策数据源接入
  2. 分析智能体层:策略规则驱动的模式匹配分析
  3. 应用智能体层:用户友好的查询接口

设计特点:

  • ✅ 模块化设计,数据源可替换
  • ✅ 预留AI服务接入点
  • ✅ 多国政策数据统一管理
  • ✅ 灵活的分析规则配置

📦 安装

# 通过ClawHub安装
clawhub install huimai-southeast-asia-policy

# 体验惠迈智能体协作模式
@惠迈智能体 查询新加坡投资政策

配置

创建配置文件 config/southeast-asia-policy.json

{
  "dataSources": {
    "type": "local|api|custom",
    "endpoint": "optional-data-source-url",
    "apiKey": "optional-data-source-key"
  },
  "countries": ["SG", "MY", "TH", "VN", "PH"],
  "updateInterval": 3600,
  "language": "zh-CN"
}

使用方法

基本查询

// 查询马来西亚最新政策
const policies = await skill.queryPolicies("Malaysia", {
  category: "investment",
  year: 2026
});

// 获取新加坡市场分析
const analysis = await skill.analyzeMarket("Singapore", "technology");

命令行使用

# 查询泰国投资政策
claw skill southeast-asia-policy query --country Thailand --category investment

# 查看越南政策信息
claw skill southeast-asia-policy query --country Vietnam

🤖 在OpenClaw中使用(惠迈智能体模式)

# 传统方式
@agent 查询新加坡最新的科技政策

# 惠迈智能体协作模式(推荐)
@惠迈智能体 对比马来西亚和泰国投资环境

# "怎么能行"实践
@惠迈智能体 如何在越南快速开展业务?
@惠迈智能体 菲律宾市场准入有什么捷径?

🎯 惠迈智能体协作案例

案例:跨境电商政策分析

用户:@惠迈智能体 我想在东南亚做跨境电商,有什么政策要注意?

智能体协作流程:
1. 数据智能体 → 整理各国电商法规信息
2. 分析智能体 → 规则匹配分析关键风险点
3. 应用智能体 → 生成定制化建议

结果:10分钟内获得完整政策分析和行动方案

API参考

queryPolicies(country, options)

查询指定国家的政策法规。

参数:

  • country (string): 国家名称或代码
  • options (object): 查询选项
    • category (string): 政策类别
    • year (number): 年份
    • keywords (array): 关键词

返回:

{
  "country": "Singapore",
  "policies": [
    {
      "title": "Singapore Technology Innovation Act 2026",
      "category": "technology",
      "issuedDate": "2026-01-15",
      "summary": "Promotes technology innovation and digital transformation",
      "url": "https://example.com/policy/123"
    }
  ]
}

analyzeMarket(country, industry)

分析指定国家特定行业的市场环境。

参数:

  • country (string): 国家名称
  • industry (string): 行业分类

返回: 市场分析报告

依赖项

  • Node.js 18+
  • axios: ^1.6.0
  • cheerio: ^1.0.0
  • cron: ^3.0.0

开发

# 克隆仓库
git clone https://gitee.com/yezhaowang888/huimai-skills.git

# 安装依赖
npm install

# 运行测试
npm test

# 构建
npm run build

贡献

欢迎提交Issue和Pull Request。

许可证

MIT License

版本历史

  • v1.0.1 (2026-04-24): 修正描述,强调框架定位
  • v1.0.0 (2026-04-22): 初始发布,支持7个东南亚国家

🎯 惠迈智能体协作案例

案例:跨境电商快速市场准入

业务场景:中国电商公司计划进入泰国市场,需要快速了解电商法规、税务政策、物流要求。

传统方式痛点

  • 需要雇佣泰国本地律师团队
  • 调研周期2-3周
  • 费用约$8000-$15000
  • 信息可能不全面或过时

惠迈智能体解决方案

  1. 数据智能体:整合泰国商务部、税务局、海关公开法规信息
  2. 分析智能体:规则分析要点、评估合规要求
  3. 应用智能体:生成定制化市场准入报告,包含具体行动步骤

效率对比

  • 时间:3周 → 15分钟(效率提升99.9%)
  • 成本:$10000 → $0(成本减少100%)

"怎么能行"实践

当用户问"如何在东南亚快速开展业务?"时:

  • 传统回答:需要详细调研、本地团队、长时间准备
  • 惠迈智能体回答:立即启动智能体协作,10分钟内给出可行方案

🔮 未来扩展

预留扩展能力:

  • 集成AI政策趋势预测(需接入AI服务)
  • 智能风险评估报告(需接入AI服务)
  • 自动化合规检查(需接入数据源)
  • 实时政策预警系统(需接入数据源)

支持

如有问题,请提交Issue或联系维护团队。


惠迈智能体:让跨境业务变得简单

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