What is weather-data?

This Claude skill enables seamless retrieval and analysis of real-time weather data and global forecasts. Designed for high-performance integration, it allows AI agents and Chainlit applications to access detailed meteorological metrics—including temperature, humidity, wind speed, and atmospheric pressure—without the need for complex API authentication, making it an essential tool for context-aware automation.

When should I use weather-data?

weather-data is useful in the following scenarios: • Case 1: Enhancing AI chatbots with real-time local weather updates to provide users with immediate, location-specific environmental context. • Case 2: Automating weather-dependent logistics and event planning by programmatically fetching multi-day forecasts to mitigate operational risks. • Case 3: Integrating meteorological analytics into business intelligence workflows to analyze the impact of weather patterns on regional sales or activities. • Case 4: Building personalized daily briefing agents that summarize current conditions, sunrise/sunset times, and 'feels like' temperatures for specific coordinates.

name	weather-data
description	Fetch and analyze weather data for specified locations. Use when you need current weather conditions, forecasts, or weather-related analytics for decision-making or integration with Chainlit chat responses.

Weather Data Skill

Purpose

This skill enables fetching and analyzing real-time weather data from public APIs. It's useful for:

Getting current weather conditions for any location
Retrieving weather forecasts
Integrating weather data into Chainlit chat responses
Performing weather-based analytics

How to Use This Skill

1. Fetch Current Weather

Use the helper script to get current weather for a location:

python scripts/fetch_weather.py --location "London" --units metric

2. Available Parameters

--location: City name or coordinates (required)
--units: metric (Celsius) or imperial (Fahrenheit), default: metric
--lang: Language for response, default: en

3. Output Format

Returns JSON with:

Temperature, feels like temperature
Weather condition and description
Humidity and pressure
Wind speed and direction
Sunrise/sunset times
Data collection timestamp

Example Integration with Chainlit

import subprocess
import json

async def get_weather_response(location: str):
    # Call the weather skill
    result = subprocess.run(
        ["python", "scripts/fetch_weather.py", "--location", location],
        capture_output=True,
        text=True
    )

    if result.returncode == 0:
        weather_data = json.loads(result.stdout)
        return format_weather_message(weather_data)
    else:
        return f"Could not fetch weather for {location}"

def format_weather_message(data):
    return f"""
    Weather in {data['city']}, {data['country']}:
    - Temperature: {data['temp']}°C (feels like {data['feels_like']}°C)
    - Condition: {data['description']}
    - Humidity: {data['humidity']}%
    - Wind: {data['wind_speed']} m/s
    """

Supported Locations

The skill supports:

City names (e.g., "London", "New York")
City, Country format (e.g., "Paris, France")
Coordinates in latitude,longitude format (e.g., "51.5074,-0.1278")

Error Handling

The script includes error handling for:

Invalid locations (returns helpful error message)
Network connectivity issues
API rate limiting
Malformed coordinates

Testing the Skill

Test with different locations:

# Major cities
python scripts/fetch_weather.py --location "Tokyo"

# With units specification
python scripts/fetch_weather.py --location "New York" --units imperial

# Using coordinates
python scripts/fetch_weather.py --location "51.5074,-0.1278"

Data Sources

Uses Open-Meteo API (free, no authentication required):

Real-time weather data
Global coverage
Accurate forecasts
No rate limiting for reasonable use

Notes

Data is cached locally for 10 minutes to improve performance
All temperature data is provided in the requested unit
Wind speeds are in m/s (metric) or mph (imperial)
Times are in UTC unless otherwise specified

weather-data

When & Why to Use This Skill

Use Cases