A Python-based integration for fetching precise meteorological data and forecasts from MET Norway via coordinate-based lookups.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install yr-weather
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 yr-weather 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 Yr.no Weather Forecast?
The yr-weather skill is a robust technical solution designed to provide AI agents with direct access to weather data from the Norwegian Meteorological Institute (MET) via the yr.no API. This skill is a vital addition to the Openclaw Skills library, offering developers a reliable way to retrieve current atmospheric conditions, precipitation levels, and wind speeds without the complexity of managing API keys.
Architected with a focus on modularity, the skill includes a dedicated service layer for API communication and a utility layer for data transformation. It enforces strict coordinate-based lookups to ensure precision, making it an ideal choice for location-aware applications that require high-fidelity climate information. By using this tool within the Openclaw Skills ecosystem, users can automate environmental monitoring and weather-dependent workflows with ease.
Yr.no Weather Forecast Use Cases
- Retrieving real-time temperature and precipitation data for precise latitude and longitude coordinates.
- Generating concise 24-hour weather summaries for automated scheduling and travel planning.
- Providing AI agents with ground-truth environmental data to support geographic research and analysis.
- Enhancing coordinate-aware Openclaw Skills with live meteorological context.
How Yr.no Weather Forecast Works
- The user or AI agent executes the script by providing specific latitude and longitude coordinates.
- The system initiates a request to the MET Norway API, including a mandatory User-Agent for identification.
- The service layer fetches the meteorological JSON payload and handles any network-level exceptions.
- The utility module parses the raw data, mapping weather codes to human-readable summaries and visual symbols.
- The final output is presented as either a detailed current forecast or a simplified daily summary.
Yr.no Weather Forecast Setup
To install the skill as a standalone package via pip:
pip install git+https://github.com/brandoncrabpi/yr-weather.git
To run the weather script locally using Python:
# Fetch current weather and forecast
python3 scripts/weather.py <lat> <lon> [altitude]
# Fetch tomorrow's summary
python3 scripts/tomorrow.py <lat> <lon>
Ensure you adhere to the 10-minute caching requirement recommended by MET Norway.
Yr.no Weather Forecast Data Schema & Taxonomy
The skill organizes its internal logic and data flow through the following components:
| File | Functionality |
|---|---|
yr_service.py |
Core service for managing API requests and response validation. |
utils.py |
Utility functions for formatting strings and mapping weather symbols. |
weather.py |
Main CLI tool for retrieving detailed forecast time-series data. |
tomorrow.py |
Specialized script for generating a concise next-day weather overview. |
tests/data/ |
Directory containing sample JSON payloads for offline development and testing. |
Yr.no Weather Forecast Advanced Features
- Support for altitude-aware forecasting to improve accuracy in varied topographical regions.
- Comprehensive unit testing suite with mocked network responses for reliable CI/CD integration.
- Minimalist footprint optimized for seamless inclusion in multi-agent Openclaw Skills pipelines.
- Built-in compliance logic including automated User-Agent headers and recommended caching intervals.
SKILL.md
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