amap-lbs-skill▌
amap-web/amap-lbs-skill · updated May 11, 2026
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高德地图综合服务向开发者提供完整的地图数据服务,包括地点搜索、路径规划、旅游规划和数据可视化等功能。
高德地图综合服务 Skill
高德地图综合服务向开发者提供完整的地图数据服务,包括地点搜索、路径规划、旅游规划和数据可视化等功能。
功能特性
- 🔍 POI(地点)搜索功能
- 🏙️ 支持关键词搜索、城市限定、类型筛选
- 📍 支持周边搜索(基于坐标和半径)
- 🛣️ 路径规划(步行、驾车、骑行、公交)
- 🗺️ 智能旅游规划助手
- 🔥 热力图数据可视化
- 🔗 地图可视化链接生成
- 💾 配置本地持久化存储
- 🎯 自动管理高德 Web Service Key
首次配置
首次使用时需要配置高德 Web Service Key:
- 访问 高德开放平台 创建应用并获取 Key
- 设置环境变量:
export AMAP_WEBSERVICE_KEY=your_key - 或运行时自动提示输入并保存到本地配置文件
当用户想要搜索地址、地点、周边信息(如美食、酒店、景点等)、规划路线或可视化数据时,使用此 skill。
触发条件
用户表达了以下意图之一:
- 搜索某类地点或某个确定地点(如"搜美食"、"找酒店"、"天安门在哪")
- 基于某个位置搜索周边(如"西直门周边美食"、"北京南站附近酒店")
- 规划路线(如"从天安门到故宫怎么走"、"规划驾车路线")
- 旅游规划(如"帮我规划北京一日游"、"杭州西湖游览路线")
- 包含"搜"、"找"、"查"、"附近"、"周边"、"路线"、"规划"等关键词
- 希望将地理数据可视化为热力图(如"生成热力图"、"用这份数据做热力图展示")
场景判断
收到用户请求后,先判断属于哪个场景:
- 场景一:用户搜索一个明确的类别(美食、酒店)或确定的地点(天安门、西湖),没有指定"在哪个位置附近"
- 场景二:用户搜索某个位置周边的某类地点,输入中同时包含「位置」和「搜索类别」两个要素(如"西直门周边美食"、"北京南站附近酒店")
- 场景三:热力图数据可视化
- 场景四:POI 详细搜索(使用 Web 服务 API)
- 场景五:路径规划
- 场景六:智能旅游规划
场景一:明确关键词搜索
直接搜索一个类别或地点,不涉及特定位置的周边搜索。
URL 格式:
https://www.amap.com/search?query={关键词}
- 域名:
www.amap.com - 路由:
/search - 参数:
query= 搜索关键词
执行步骤
- 提取关键词:从用户输入中识别出核心搜索词,去掉"搜"、"找"等修饰词
- 生成 URL:拼接
https://www.amap.com/search?query={关键词} - 返回链接给用户
示例
| 用户输入 | 提取关键词 | 生成 URL |
|---|---|---|
| 搜美食 | 美食 | https://www.amap.com/search?query=美食 |
| 找酒店 | 酒店 | https://www.amap.com/search?query=酒店 |
| 天安门在哪 | 天安门 | https://www.amap.com/search?query=天安门 |
| 找个加油站 | 加油站 | https://www.amap.com/search?query=加油站 |
回复模板
🔍 已为你生成高德地图搜索链接:
https://www.amap.com/search?query={关键词}
点击链接即可查看搜索结果。
场景二:基于位置的周边搜索
用户想搜索某个位置周边的某类地点。需要先通过地理编码 API 获取该位置的经纬度,再拼接带坐标的搜索链接。
前置条件: 需要用户提供高德开放平台的 API Key。
执行步骤
第一步:解析用户输入
从用户输入中拆分出两个要素:
- 位置:用户指定的中心位置(如"西直门"、"北京南站")
- 搜索类别:要搜索的内容(如"美食"、"酒店")
| 用户输入 | 位置 | 搜索类别 |
|---|---|---|
| 西直门周边美食 | 西直门 | 美食 |
| 北京南站附近酒店 | 北京南站 | 酒店 |
| 天坛周边有什么好吃的 | 天坛 | 美食 |
第二步:检查 API Key
- 如果用户之前未提供过 Key,先提示用户提供高德 API Key,等待用户回复后再继续
- 如果用户已提供 Key,直接使用
请求 Key 的回复模板:
🔑 搜索「{位置}」周边的{搜索类别}需要使用高德 API,请提供你的高德开放平台 API Key。
(如果还没有 Key,可以在 https://lbs.amap.com 注册并创建应用获取)
第三步:调用地理编码 API 获取经纬度
API 格式:
https://restapi.amap.com/v3/geocode/geo?address={位置}&output=JSON&key={用户的key}
执行 curl 请求:
curl -s "https://restapi.amap.com/v3/geocode/geo?address={位置}&output=JSON&key={用户的key}"
API 返回示例:
{
"status": "1",
"info": "OK",
"geocodes": [
{
"formatted_address": "北京市西城区西直门",
"location": "116.353138,39.939385"
}
]
}
从返回结果中提取 geocodes[0].location,格式为 经度,纬度(如 116.353138,39.939385),拆分为:
- 经度(longitude):
116.353138 - 纬度(latitude):
39.939385
第四步:拼接带坐标的搜索链接
URL 格式:
https://ditu.amap.com/search?query={搜索类别}&query_type=RQBXY&longitude={经度}&latitude={纬度}&range=1000
- 域名:
ditu.amap.com - 路由:
/search - 参数:
query= 搜索类别(如"美食")query_type=RQBXY(基于坐标的搜索类型)longitude= 经度latitude= 纬度range= 搜索范围(单位:米,默认 1000)
第五步:返回链接给用户
完整示例
用户输入: "搜索西直门周边美食"
- 解析:位置 =
西直门,搜索类别 =美食 - 调用地理编码 API:
curl -s "https://restapi.amap.com/v3/geocode/geo?address=西直门&output=JSON&key=xxx" - 获取坐标:
116.353138,39.939385→ 经度116.353138,纬度39.939385 - 拼接链接:
https://ditu.amap.com/search?query=美食&query_type=RQBXY&longitude=116.353138&latitude=39.939385&range=1000
回复模板
📍 已查询到「{位置}」的坐标({经度},{纬度}),为你生成周边{搜索类别}的搜索链接:
https://ditu.amap.com/search?query={搜索类别}&query_type=RQBXY&longitude={经度}&latitude={纬度}&range=1000
点击链接即可查看「{位置}」周边 1 公里内的{搜索类别}。
场景三:热力图展示
用户有一份包含地理坐标的数据,希望在地图上以热力图的形式可视化展示。
触发条件
用户提到"热力图"、"数据可视化"、"地图上展示数据"等意图,并提供了数据地址。
URL 格式
http://a.amap.com/jsapi_demo_show/static/openclaw/heatmap.html?mapStyle={地图风格}&dataUrl={数据地址(URL编码)}
- 域名:
a.amap.com - 路由:
/jsapi_demo_show/static/openclaw/heatmap.html - 必填参数:
dataUrl= 用户数据的 URL 地址(必须进行 URL 编码)mapStyle= 地图风格,可选值:grey— 暗黑地图模式(深色背景,适合展示亮色热力点)light— 浅色模式(浅色背景,适合日常查看)
执行步骤
- 获取数据地址:从用户输入中提取数据 URL,如果用户未提供,提示用户给出数据地址
- 确认地图风格:询问用户偏好的地图风格(
grey或light),如果用户未指定,默认使用grey - URL 编码:将数据地址进行 URL 编码(将
://→%3A%2F%2F,/→%2F等) - 拼接链接:生成完整的热力图 URL
- 返回链接给用户
示例
用户输入: "帮我用这份数据生成热力图:https://a.amap.com/Loca/static/loca-v2/demos/mock_data/hz_house_order.json,用暗黑模式"
- 数据地址:
https://a.amap.com/Loca/static/loca-v2/demos/mock_data/hz_house_order.json - 地图风格:
grey - URL 编码后的数据地址:
https%3A%2F%2Fa.amap.com%2FLoca%2Fstatic%2Floca-v2%2Fdemos%2Fmock_data%2Fhz_house_order.json - 最终链接:
http://a.amap.com/jsapi_demo_show/static/openclaw/heatmap.html?mapStyle=grey&dataUrl=https%3A%2F%2Fa.amap.com%2FLoca%2Fstatic%2Floca-v2%2Fdemos%2Fmock_data%2Fhz_house_order.json
回复模板
🔥 已为你生成热力图链接:
http://a.amap.com/jsapi_demo_show/static/openclaw/heatmap.html?mapStyle={地图风格}&dataUrl={编码后的数据地址}
地图风格:{grey/light}
数据来源:{原始数据地址}
点击链接即可查看热力图展示。
请求数据地址的回复模板(用户未提供时):
🔥 生成热力图需要你提供数据地址(JSON 格式的 URL),请给出数据链接。
另外,你希望使用哪种地图风格?
- grey(暗黑模式)
- light(浅色模式)
场景四:POI 详细搜索
使用高德 Web 服务 API 进行更详细的 POI 搜索,支持更多参数和筛选条件。
使用方法
# 基础搜索
node scripts/poi-search.js --keywords=肯德基 --city=北京
# 搜索更多结果
node scripts/poi-search.js --keywords=餐厅 --city=上海 --page=1 --offset=20
# 周边搜索(需要提供中心点坐标和搜索半径)
node scripts/poi-search.js --keywords=酒店 --location=116.397428,39.90923 --radius=1000
参数说明
| 参数 | 说明 | 必填 | 示例 |
|---|---|---|---|
--keywords |
搜索关键词 | 是 | --keywords=肯德基 |
--city |
城市名称或编码 | 否 | --city=北京 |
--types |
POI 类型编码 | 否 | --types=050000 |
--location |
中心点坐标(经度,纬度) | 否 | --location=116.397428,39.90923 |
--radius |
搜索半径(米) | 否 | --radius=1000 |
--page |
页码 | 否 | --page=1 |
--offset |
每页数量(最大25) | 否 | --offset=10 |
在代码中使用
const { searchPOI } = require('./index');
async function example() {
const result = await searchPOI({
keywords: '咖啡厅',
city: '杭州',
page: 1,
offset: 10
});
if (result && result.pois) {
result.pois.forEach(poi => {
console.log(`${poi.name} - ${poi.address}`);
});
}
}
example();
场景五:路径规划
规划不同出行方式的路线。
使用方法
# 步行路线
node scripts/route-planning.js --type=walking --origin=116.397428,39.90923 --destination=116.427281,39.903719
# 驾车路线
node scripts/route-planning.js --type=driving --origin=116.397428,39.90923 --destination=116.427281,39.903719
# 公交路线
node scripts/route-planning.js --type=transfer --origin=116.397428,39.90923 --destination=116.427281,39.903719 --city=北京
路线类型
walking- 步行路线driving- 驾车路线riding- 骑行路线transfer- 公交路线(需要指定城市)
场景六:智能旅游规划
自动搜索兴趣点并规划游览路线,生成地图可视化链接。
使用方法
# 基础旅游规划
node scripts/travel-planner.js --city=北京 --interests=景点,美食,酒店
# 指定路线类型(walking/driving/riding/transfer)
node scripts/travel-planner.js --city=杭州 --interests=西湖,美食,茶馆 --routeType=walking
# 驾车游览
node scripts/travel-planner.js --city=上海 --interests=外滩,南京路,城隍庙 --routeType=driving
功能说明
- 自动搜索指定城市的兴趣点(每类最多5个)
- 按顺序规划各兴趣点之间的路线
配置管理
配置文件位于 config.json,包含以下内容:
{
"webServiceKey": "your_amap_webservice_key_here"
}
设置 Key 的方式:
- 环境变量:
export AMAP_WEBSERVICE_KEY=your_key - 命令行参数:
node index.js your_key - 自动提示:首次运行时自动提示输入
- 手动编辑:直接编辑
config.json文件
注意事项
- 场景判断是关键:区分用户是"直接搜某个东西"、"在某个位置附近搜某个东西"、"规划路线"还是"旅游规划"
- 关键词应尽量精简准确,提取用户真正想搜的内容
- URL 中的中文关键词浏览器会自动处理编码,无需手动 encode
- 场景二、四、五、六需要用户提供高德 API Key,必须先获取 Key 后再发起请求,不能跳过
- 如果地理编码 API 返回
status不为"1",说明请求失败,需提示用户检查 Key 是否正确或地址是否有效 - API 返回的
location格式为经度,纬度(注意:经度在前,纬度在后) - 场景二的搜索范围默认 1000 米,用户如有需要可调整
range参数 - 请妥善保管你的 Web Service Key,不要分享给他人
- 高德 Web 服务 API 有调用频率限制,请合理使用
- 免费用户每日调用量有限制,具体请查看高德开放平台说明
相关链接
How to use amap-lbs-skill on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add amap-lbs-skill
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches amap-lbs-skill from GitHub repository amap-web/amap-lbs-skill and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate amap-lbs-skill. Access the skill through slash commands (e.g., /amap-lbs-skill) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★59 reviews- ★★★★★Chen Yang· Dec 20, 2024
We added amap-lbs-skill from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Sakura Mehta· Dec 20, 2024
amap-lbs-skill reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ama Diallo· Dec 16, 2024
We added amap-lbs-skill from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Pratham Ware· Dec 8, 2024
Useful defaults in amap-lbs-skill — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Liam Ghosh· Dec 8, 2024
Useful defaults in amap-lbs-skill — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Liam Reddy· Dec 4, 2024
Registry listing for amap-lbs-skill matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Luis Anderson· Dec 4, 2024
amap-lbs-skill has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Anika Patel· Dec 4, 2024
Solid pick for teams standardizing on skills: amap-lbs-skill is focused, and the summary matches what you get after install.
- ★★★★★Sakshi Patil· Nov 27, 2024
amap-lbs-skill has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Valentina Sharma· Nov 27, 2024
amap-lbs-skill has been reliable in day-to-day use. Documentation quality is above average for community skills.
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