A specialized weather data integration for fetching forecasts, historical trends, and site-specific risk assessments for construction project management.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install weather-api-1
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 weather-api-1 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 Weather API?
This Openclaw Skills integration provides a robust interface for accessing meteorological data tailored specifically for the construction industry. Since weather impacts approximately 50% of all construction activities, this skill bridges the gap between raw atmospheric data and actionable project management. It allows developers and project managers to programmatically retrieve historical trends and future forecasts to mitigate delays and optimize site safety.
By leveraging the Open-Meteo API, the skill provides a Python-based client to evaluate workability based on specific environmental thresholds. Whether you are managing concrete pours, crane operations, or exterior painting, this Openclaw Skills resource ensures that weather-related risks are quantified and integrated directly into your automated workflows, allowing for data-driven decision making in the field.
Weather API Use Cases
- Schedule Planning: Automatically check for optimal weather windows for sensitive tasks like concrete pouring or roofing to avoid material failure.
- Historical Trend Analysis: Analyze past weather patterns to estimate potential seasonal delays for future project bids and contract negotiations.
- Real-time Risk Assessment: Monitor upcoming conditions to trigger safety alerts for high-wind crane operations or extreme heat protocols.
- Productivity Adjustments: Calculate expected workable hours based on precipitation and temperature forecasts to manage labor costs efficiently.
How Weather API Works
- The Weather API Client connects to the Open-Meteo backend to fetch hourly meteorological data for specific GPS coordinates.
- Raw data including temperature, humidity, wind speed, and precipitation is parsed into structured Python dataclasses for high type safety.
- The Construction Weather Risk engine applies industry-specific thresholds to the data (e.g., assessing if temperatures are too low for concrete hydration).
- A Workability Assessment is generated, categorizing risk levels from Low to Critical based on the number of affected activities.
- The final output provides specific recommendations and affected activity lists, which can be exported to Pandas DataFrames for reporting within Openclaw Skills environments.
Weather API Setup
To get started with this skill on Openclaw Skills, ensure you have the required Python dependencies installed in your environment.
pip install requests pandas
Once installed, you can initialize the client and begin fetching weather data immediately without complex API keys for basic tiers:
from weather_api import WeatherAPIClient
weather = WeatherAPIClient()
# Get a 7-day forecast for your site coordinates
conditions = weather.get_forecast(latitude=52.52, longitude=13.41, days=7)
Weather API Data Schema & Taxonomy
The skill organizes data into structured formats that facilitate both automated processing and human-readable reporting.
| Attribute | Description | Data Type |
|---|---|---|
| timestamp | The specific hour or date of the weather record | datetime |
| risk_level | The assessed danger for construction (LOW to CRITICAL) | Enum |
| workable_hours | The estimated number of hours viable for outdoor work | int |
| affected_activities | List of specific tasks (e.g., 'concrete_pour') impacted | list |
| precipitation | Recorded or forecasted rainfall in millimeters | float |
Weather API Advanced Features
- Activity-Specific Thresholds: Pre-defined logic for concrete pouring, crane work, painting, roofing, and earthwork based on industrial safety standards.
- Historical Archive Access: Deep-dive into years of past weather data to build more accurate project timelines.
- Native Pandas Integration: Seamlessly convert weather conditions into DataFrames for advanced data science and visualization.
- Multi-Factor Risk Scoring: Aggregates wind, temperature, and rain to provide a holistic 'Workability Assessment' rather than just raw numbers.
SKILL.md
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