City Walker is an intelligent urban exploration assistant that creates curated, walking-friendly routes to discover hidden city gems.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install city-walker
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 city-walker 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 City Walker?
City Walker is a sophisticated AI skill designed for urban explorers who want to experience cities beyond the typical tourist maps. By leveraging the flyai protocol, this skill identifies hidden corners, boutique cafes, and historical landmarks to synthesize half-day or full-day micro-travel plans. It is a premier example of how Openclaw Skills can transform raw geographic data into personalized, mood-based walking experiences for weekend outings, business trip gaps, or local residents seeking new perspectives on their own neighborhoods.
The skill excels at balancing technical route optimization with human-centric storytelling. It doesn't just provide coordinates; it weaves together themes like architecture, independent bookstores, and night markets into a cohesive narrative. By utilizing the Openclaw Skills framework, it ensures every route is walking-friendly, avoiding major highways in favor of charming alleys and pedestrian paths.
City Walker Use Cases
- Planning spontaneous afternoon walks when you want to explore your local surroundings.
- Finding hidden gems or niche attractions that are not highlighted on standard digital maps.
- Organizing themed micro-trips like independent bookstore tours or architecture photography walks.
- Discovering quiet, healing spots for solo relaxation or zoning out in a busy city.
- Generating walking routes for travelers with limited time, such as half-day gaps during business trips.
How City Walker Works
- The user provides a starting point, such as a current location, hotel, or subway station, along with a desired mood or theme.
- The skill utilizes Openclaw Skills capabilities to search for Points of Interest (POIs) using flyai search-poi and keyword-search commands.
- Routes are optimized based on walking friendliness, ensuring segments are between 5-15 minutes apart and total distances remain manageable (3-8 km).
- The AI organizes the route into a logical sequence, typically consisting of a convenient start, 2-3 core exploration points, and a relaxing endpoint like a cafe or park.
- A final itinerary is generated including estimated times, photography tips, and practical amenities like nearby restrooms or transit return routes.
City Walker Setup
To enable City Walker, ensure you have the flyai requirement configured within your environment. The skill uses the following logic to fetch data through Openclaw Skills integrations:
# Example of how the agent searches for local gems via flyai
flyai search-poi --city-name "Shanghai" --keyword "boutique coffee" --category "cafe"
# Searching for thematic recommendations
flyai keyword-search --query "Beijing historical hutong walking route recommendations"
City Walker Data Schema & Taxonomy
The skill organizes urban data into a structured format for clear user consumption:
| Component | Description |
|---|---|
| Route Overview | Summary including start/end points, total duration, and distance. |
| Text-Based Map | A visual step-by-step timeline of the walking path with interval times. |
| Spot Details | Specific information on features, recommended stay time, and photography angles. |
| Practical Info | Best visiting hours for lighting, dress code suggestions, and essential gear (power banks, umbrellas). |
| Random Surprises | Hidden Easter eggs or unlisted shops found along the route. |
City Walker Advanced Features
- Improvised Walk Mode: Dynamically generates routes based on real-time mood and available time without a fixed destination.
- City Puzzle System: Encourages users to collect and complete routes across different districts to map out an entire city.
- Seasonal Route Adaptation: Automatically suggests routes tailored to spring flowers, summer shade, autumn leaves, or indoor winter warmth.
- Solo-Friendly Indicators: Specifically highlights restaurants and spaces where single explorers can feel comfortable.
- Real-time Safety Awareness: Integrates with Openclaw Skills to recommend well-lit, populated paths and provides operating hours to avoid closed venues.
SKILL.md
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