An intelligent travel route planning assistant that provides structured transport options, smart filtering, and time conflict detection using the Amap API.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install route-assistant
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install route-assistant using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Route Assistant?
Route Assistant is a powerful navigation and logistics tool designed to simplify complex travel planning within the ecosystem of Openclaw Skills. By leveraging the Amap (高德地图) Geocoding and Direction APIs, it transforms simple natural language queries into a comprehensive, three-part travel itinerary. This skill is specifically engineered to provide technical clarity, offering users a high-level overview of transport methods alongside granular details for driving, public transit, walking, and taxi options.
Beyond basic navigation, the skill excels at intelligent decision-making. It doesn't just list routes; it evaluates them against feasibility thresholds and time constraints. Whether you are building an automated travel agent or a personal productivity tool, this addition to your Openclaw Skills library ensures that travel data is presented in a structured, actionable format that accounts for real-world variables like distance and departure schedules.
Route Assistant Use Cases
- Comparing multiple transport methods for daily commutes or business trips.
- Planning time-sensitive travel to catch flights or trains with automated conflict warnings.
- Quickly identifying the best walking routes for short-distance urban navigation.
- Automating location-based research and travel time estimation within AI agent workflows using Openclaw Skills.
How Route Assistant Works
- The skill parses the user's natural language input to identify origins, destinations, and specific transport preferences.
- It utilizes the Amap Geocoding API to convert location names into precise geographical coordinates.
- The tool queries the Amap Direction API v5 to retrieve real-time distance and path data for all supported transport modes.
- It applies intelligent filtering logic to hide impractical options (e.g., walking for distances over 3km or taxis for distances under 1km).
- It performs time conflict analysis if specific departure or arrival times (like flight numbers) are provided.
- The final output is rendered in a structured three-part format: a transport summary table, recommended schemes, and critical reminders.
Route Assistant Setup
To deploy this skill within your environment, ensure you have valid Amap API credentials. Use the following steps to integrate it with your Openclaw Skills setup:
# Install the route-assistant skill
openclaw install route-assistant
# Configure your Amap API key in your environment variables
export AMAP_API_KEY='your_api_key_here'
Once configured, the agent will respond to triggers like "how to get to..." or specific location-based queries.
Route Assistant Data Schema & Taxonomy
The skill organizes travel data into three distinct sections for maximum readability:
| Section | Description | Data Content |
|---|---|---|
| Transport Table | Comparative overview | Mode, Distance (km), Duration (min), Details |
| Recommended Schemes | Feasibility-filtered list | Sorted by travel time, removes impractical options |
| Important Reminders | Contextual alerts | Suggested departure times, time conflict warnings, and flight/train info |
Route Assistant Advanced Features
- Smart recognition of flight and train numbers to sync travel routes with specific transit schedules.
- Automated duration estimation using Amap API v5 distance data and intelligent speed heuristics.
- Dynamic filtering logic that optimizes results based on distance thresholds (e.g., walking vs. driving).
- Seamless multi-lingual support for both Chinese and English triggers within the Openclaw Skills framework.
SKILL.md
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