@GoSailGlobal: Chinese AI Agents Most Lack the Ability to Access Local Real Data. Amap just opened a door: amap-lbs-skill, adapted for OpenClaw platform, MIT license, 9 stars, packages five things: POI search, route planning (walking/driving/cycling/bus…)

X AI KOLs Timeline Tools

Summary

Amap officially released amap-lbs-skill, an open-source toolkit (MIT license) adapted for the OpenClaw platform, providing five types of map data services including POI search, route planning, and trip planning, enabling AI Agents to directly call real local geographic data in China and output visual map links.

Chinese AI Agents most lack the ability to access local real data. Amap just opened a door amap-lbs-skill, adapted for OpenClaw platform, MIT license, 9 stars Packages five things: POI search Route planning (walking / driving / cycling / transit) Smart trip planning assistant Nearby search Heatmap data visualization · The calling interface follows the Skill standard format SKILL.md / scripts/ / index.js, configure an Amap Web Service Key and it runs Any Agent that uses Claude Skill / OpenClaw Skill format can directly connect · Another major Chinese company is adopting Skill integration The five services, when connected to an Agent, enable real-world scenarios POI search → "List all Michelin restaurants in Shanghai", "Top 10 coffee shops near 798 by rating", "How many pediatric hospitals within 1km of my home" Route planning → "Visit 5 clients in Beijing tomorrow, optimize route by shortest time", "How to walk the West Lake one-day tour with least fatigue", "From Pudong Airport to the Bund, which is faster: driving or subway" Smart trip planning → "Plan a 3-day Chengdu trip with attractions + food + route + map link", "48-hour Tokyo weekend itinerary on a budget of 5000 RMB" Nearby search → "Is there a convenience store within 500m of the hotel", "Nearest charging station to my current location", "Coffee shop near the meeting room that is drive-through accessible" Heatmap visualization → "Generate a heatmap of pet hospital distribution in Shanghai", "Plot customer data on a map to see which area has the highest sales density", "Highlight top 10 neighborhoods by convenience store density" · The five services together equal one thing AI Agents in mainland China finally "can get work done" and produce visual results Travel guides upgrade from plain text to visual map links with POIs and routes, ready to share and use · http://github.com/AMap-Web/amap-lbs-skill…
Original Article
View Cached Full Text

Cached at: 05/23/26, 12:10 PM

The most lacking capability for AI Agents in the Chinese market right now is the ability to access real local data. AMap (Gaode Maps) has just opened a gateway: amap-lbs-skill, adapted for the OpenClaw platform, MIT license, with 9 stars. It packs five capabilities:

  • POI search
  • Route planning (walking/driving/cycling/public transit)
  • Intelligent travel planner
  • Nearby search
  • Heatmap data visualization

The invocation follows the Skill standard format: SKILL.md, scripts/, index.js — just configure an AMap Web Service Key and it runs. Any Agent that uses the Claude Skill or OpenClaw Skill interface can connect directly. Another major Chinese tech company has stepped into providing Skill integrations.

Those five capabilities, when connected to an Agent, enable real-world scenarios:

  • POI search → “List all Michelin restaurants in Shanghai”, “Top 10 cafes near 798”, “How many pediatric hospitals within 1km of my home?”
  • Route planning → “Visit 5 clients in Beijing tomorrow, optimize route by shortest time”, “Best route for a one-day West Lake tour without getting tired”, “From Pudong airport to The Bund, driving vs subway — which is faster?”
  • Intelligent travel planner → “3-day trip in Chengdu, give me attractions + food + route + map links”, “48-hour Tokyo weekend, budget ¥5000, create itinerary”
  • Nearby search → “Any convenience stores within 500m of the hotel?”, “Nearest EV charging station to my current location”, “A café near the meeting room that allows drive-in”
  • Heatmap visualization → “Generate a heatmap of pet hospitals in Shanghai”, “Plot customer data on map to see which area has highest sales density”, “Highlight top 10 neighborhoods by convenience store density”

Combined, these five capabilities mean one thing: AI Agents in mainland China can finally “get things done” and produce visual results. Travel guides upgrade from plain text to visual map links with POIs and routes, ready to share.

http://github.com/AMap-Web/amap-lbs-skill…


AMap-Web/amap-lbs-skill

Source: https://github.com/AMap-Web/amap-lbs-skill

AMap LBS Skill

AMap LBS Skill provides developers with comprehensive map data services, including location search, route planning, travel planning, and data visualization.

Features

  • ✅ Automatic AMap Web Service Key management
  • ✅ POI search
  • ✅ Route planning (walking, driving, cycling, public transit)
  • ✅ Intelligent travel planner
  • ✅ Map visualization link generation
  • ✅ Heatmap data visualization
  • ✅ Command-line script execution
  • ✅ Persistent local configuration

Install dependencies

npm install

Configure API Key

You need to configure an AMap Web Service Key on first use:

# Method 1: via environment variable at runtime
export AMAP_WEBSERVICE_KEY=your_key
node scripts/poi-search.js --keywords=KFC --city=Beijing

# Method 2: runtime prompt to input (saved to config.json)
node scripts/poi-search.js --keywords=KFC --city=Beijing

# Method 3: manually create configuration file
cp config.example.json config.json
# then edit config.json and fill in your Key

Get API Key: Visit the AMap Open Platform (https://lbs.amap.com/api/webservice/create-project-and-key) to create an application and obtain a Key.

Usage

1. POI Search

# Basic search
node scripts/poi-search.js --keywords=KFC --city=Beijing

# Search with more parameters
node scripts/poi-search.js --keywords=Restaurant --city=Shanghai --page=1 --offset=20

# Nearby search (requires center point coordinates and radius)
node scripts/poi-search.js --keywords=Hotel --location=116.397428,39.90923 --radius=1000

2. Route Planning

# Walking route
node scripts/route-planning.js --type=walking --origin=116.397428,39.90923 --destination=116.427281,39.903719

# Driving route (with waypoints)
node scripts/route-planning.js --type=driving --origin=116.397428,39.90923 --destination=116.427281,39.903719 --waypoints=116.410000,39.910000

# Cycling route
node scripts/route-planning.js --type=riding --origin=116.397428,39.90923 --destination=116.427281,39.903719

# Public transit route
node scripts/route-planning.js --type=transfer --origin=116.397428,39.90923 --destination=116.427281,39.903719 --city=Beijing

3. Intelligent Travel Planner

# Basic travel planning
node scripts/travel-planner.js --city=Beijing --interests=Attractions,Food,Hotels

# Specify route type
node scripts/travel-planner.js --city=Hangzhou --interests=West Lake,Food,Tea House --routeType=walking

# Driving tour
node scripts/travel-planner.js --city=Shanghai --interests=The Bund,Nanjing Road,Chenghuang Temple --routeType=driving

4. Use in Code

const { searchPOI, walkingRoute, drivingRoute, travelPlanner, generateMapLink } = require('./index');

// POI Search
async function searchExample() {
    const result = await searchPOI({ keywords: 'KFC', city: 'Beijing', page: 1, offset: 10 });
    console.log(result);
}

// Walking route planning
async function routeExample() {
    const result = await walkingRoute({ origin: '116.397428,39.90923', destination: '116.427281,39.903719' });
    console.log(result);
}

// Travel planning
async function travelExample() {
    const result = await travelPlanner({ city: 'Beijing', interests: ['Attractions', 'Food', 'Hotels'], routeType: 'walking' });
    console.log(result.mapLink); // Map visualization link
}

// Generate map link
function mapLinkExample() {
    const mapData = [
        { type: 'poi', lnglat: [116.397428, 39.90923], sort: 'Scenic Spot', text: 'Forbidden City', remark: 'Imperial palace of Ming and Qing dynasties' },
        { type: 'route', routeType: 'walking', start: [116.397428, 39.90923], end: [116.427281, 39.903719], remark: 'Walking route' }
    ];
    const link = generateMapLink(mapData);
    console.log(link);
}

API Parameter Description

POI Search Parameters

ParameterTypeRequiredDescription
keywordsstringYesSearch keyword
citystringNoCity name or city code
typesstringNoPOI type code, separate multiple with |
locationstringNoCenter point coordinates (longitude,latitude)
radiusnumberNoSearch radius in meters
pagenumberNoCurrent page number, default 1
offsetnumberNoRecords per page, default 10, max 25

Route Planning Parameters

Walking Route (walkingRoute)

ParameterTypeRequiredDescription
originstringYesStart coordinates “longitude,latitude”
destinationstringYesEnd coordinates “longitude,latitude”

Driving Route (drivingRoute)

ParameterTypeRequiredDescription
originstringYesStart coordinates “longitude,latitude”
destinationstringYesEnd coordinates “longitude,latitude”
waypointsstringNoWaypoints, separate multiple with ;, max 16
strategynumberNoDriving strategy, default 10 (avoid congestion)

Cycling Route (ridingRoute)

ParameterTypeRequiredDescription
originstringYesStart coordinates “longitude,latitude”
destinationstringYesEnd coordinates “longitude,latitude”

Public Transit Route (transitRoute)

ParameterTypeRequiredDescription
originstringYesStart coordinates “longitude,latitude”
destinationstringYesEnd coordinates “longitude,latitude”
citystringYesCity name or city code
strategynumberNoTransit strategy, 0-5, default 0 (fastest)
nightflagbooleanNoWhether to include night buses, default false

Travel Planner Parameters (travelPlanner)

ParameterTypeRequiredDescription
citystringYesCity name
interestsarrayNoArray of interest keywords, default [‘Attractions’,‘Food’]
routeTypestringNoRoute type: walking/driving/riding/transfer, default walking

Project Structure

jsapi-skills/
├── index.js                 # Main entry file, core functions
├── scripts/
│   ├── poi-search.js        # POI search script
│   ├── route-planning.js    # Route planning script
│   └── travel-planner.js    # Intelligent travel planner script
├── config.json              # Configuration file (auto-generated, do not commit)
├── config.example.json      # Configuration example
├── package.json             # Dependency configuration
├── .gitignore               # Git ignore configuration
├── SKILL.md                 # OpenClaw Skill description file
└── README.md                # This file

Map Visualization

All planning results generate a map visualization link in the following format:

https://a.amap.com/jsapi_demo_show/static/openclaw/travel_plan.html?data=

The data format follows the MapTaskData interface specification, supporting:

  • POI tasks: display point of interest locations and information
  • Route tasks: display route planning results

Example data structure:

[
    // POI point of interest
    {
        type: 'poi',
        lnglat: [116.397428, 39.90923],
        sort: 'Scenic Spot',
        text: 'Forbidden City',
        remark: 'Imperial palace of Ming and Qing dynasties, formerly known as the Forbidden City.'
    },
    // Route planning
    {
        type: 'route',
        routeType: 'walking',
        start: [116.397428, 39.90923],
        end: [116.427281, 39.903719],
        remark: 'Walking route'
    }
]

Notes

  1. Keep your Web Service Key secure; do not commit it to public repositories.
  2. config.json is already in .gitignore and will not be committed.
  3. AMap Web Service API has call frequency limits; use reasonably.
  4. Free users have daily call limits; see the AMap Open Platform documentation for details.

Related Links

  • AMap Open Platform (https://lbs.amap.com/)
  • Create application and get Key (https://lbs.amap.com/api/webservice/create-project-and-key)
  • POI Search API documentation (https://lbs.amap.com/api/webservice/guide/api-advanced/newpoisearch)
  • Web Service API overview (https://lbs.amap.com/api/webservice/summary)

License

MIT

Jason Zhu (@GoSailGlobal):
That’s quite something

Alibaba’s AMap (Gaode Maps), someone actually submitted amap-lbs-skill to my little site

Two of the three submitted projects were accepted:

☑️ https://t.co/0V34mJKxgc
☑️ https://t.co/XluGaMH5Ay

Similar Articles

@Yuancheng: ➤ New ideas and practices for Agent Harness are still emerging. Lately I came across **OpenSquilla**, an open-source, locally-hosted AI Agent. ① It features intelligent model routing—for the same task, token cost is 60-80% less than OpenClaw …

X AI KOLs Timeline

OpenSquilla is an open-source, locally-hosted AI Agent with intelligent model routing that allocates tasks among different models to save token costs, and introduces the MetaSkill mechanism to let the Agent automatically organize skills.

@oragnes: Wow, just dug up this amazing tool map3d on GitHub! Based on OpenStreetMap, you select an area on the web page, and it automatically fetches real building and road data, rendering a 3D city model with heights in one click! The craziest part is it can directly export GLB files for use in Blender or game engines…

X AI KOLs Timeline

Introduces two open-source tools on GitHub: map3d, which automatically generates 3D city models from OpenStreetMap and exports GLB files; and Voice-Pro, a local tool integrating video download, voice separation, subtitle recognition, translation, voice cloning dubbing, and video synthesis.

@GoSailGlobal: https://x.com/GoSailGlobal/status/2058455845243847068

X AI KOLs Timeline

This week saw a flurry of AI industry news, with the core trend being that all model labs are pivoting to Agent products: AI21 shuts down its model team, DeepSeek forms a Harness team and permanently cuts the price of V4-Pro; Coding Agents enter a weekly update cycle; the MCP protocol undergoes a major overhaul toward statelessness; Google launches an Agent family; in security, AI vulnerability discovery outpaces manual fixes by a wide margin.