A specialized guidance skill for AI agents to master Mapbox search tools through optimized tool selection, parameter tuning, and spatial constraints.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install mapbox-search-patterns
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 mapbox-search-patterns 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 Mapbox Search Patterns?
Mapbox Search Patterns is a technical framework designed for Openclaw Skills that empowers AI assistants to interact effectively with Mapbox location services. It provides a structured approach to choosing between geocoding, category searches, and reverse geocoding to ensure users receive the most relevant geographical data.
By implementing these Openclaw Skills, developers can eliminate common pitfalls like global-bias errors or brand-category mismatches. The skill focuses on maximizing API efficiency while providing a superior user experience through precise spatial biasing and result filtering.
Mapbox Search Patterns Use Cases
- Finding specific brand locations like Starbucks or Target using dedicated geocoding logic.
- Discovering generic points of interest such as coffee shops or museums within a specific neighborhood.
- Converting GPS coordinates into human-readable addresses for mobile or logistics applications.
- Restricting search results to specific country boundaries or custom bounding boxes for localized service apps.
- Optimizing search-as-you-type interfaces with fuzzy matching and partial query handling.
How Mapbox Search Patterns Works
- The AI agent analyzes the user's natural language query to identify specific entities, generic categories, or coordinate data.
- Based on the query type, the agent selects the appropriate tool: search_and_geocode_tool for names, category_search_tool for types, or reverse_geocode_tool for coordinates.
- Spatial constraints are applied, prioritizing proximity biasing to ensure local relevance without strictly excluding high-value distant matches.
- Parameters such as limit, types, and country codes are configured to refine the result set according to the UI requirements.
- The skill executes the request and returns structured location data, optionally including ETA or navigation profiles if requested.
Mapbox Search Patterns Setup
To integrate these Mapbox patterns into your Openclaw Skills workflow, ensure your environment is configured with the necessary Mapbox API credentials.
# Install relevant Mapbox dependencies
npm install @mapbox/mapbox-sdk
# Configure your environment variables
export MAPBOX_ACCESS_TOKEN='your_access_token_here'
Refer to the internal reference files references/workflows.md and references/advanced-params.md for specific implementation logic.
Mapbox Search Patterns Data Schema & Taxonomy
The skill organizes its search logic and data retrieval based on the following taxonomy:
| Feature Type | Description | Best Use Case |
|---|---|---|
| poi | Points of Interest | Businesses and landmarks |
| address | Street-level data | Specific delivery or navigation targets |
| place | Cities and regions | Regional search or broad location setting |
| postcode | ZIP/Postal codes | Area-based filtering |
All results are returned in a structured format, typically leveraging proximity (longitude/latitude objects) and bbox (minLon, minLat, maxLon, maxLat) for spatial context.
Mapbox Search Patterns Advanced Features
- Multi-parameter spatial filtering combining proximity, bounding boxes, and country constraints.
- Travel-time ranking using eta_type and navigation_profile for logistics-heavy Openclaw Skills.
- Fuzzy matching via the auto_complete parameter to handle user typos and real-time search input.
- Optimized limit handling to prevent UI clutter and reduce API quota consumption.
SKILL.md
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