A utility for generating deterministic, simulated weather forecasts and current conditions for any city without requiring an external API.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install mock-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 mock-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 Mock Weather Skill?
Mock Weather Skill is a specialized utility designed to provide synthetic meteorological data for developers and AI agents. It eliminates the need for real-time API keys by generating consistent, plausible weather reports based on a combination of city names and the current date. As part of the Openclaw Skills ecosystem, it allows agents to simulate weather-related interactions in offline or restricted environments.
This skill is particularly useful for demonstrating conversational capabilities, testing conditional logic based on climate variables, and building prototypes. By using this tool within Openclaw Skills, developers can ensure their agents behave predictably while handling weather queries in both English and Chinese.
Mock Weather Skill Use Cases
- Testing weather-aware logic in AI agents without incurring API costs or hitting rate limits.
- Demonstrating search and reporting features for Openclaw Skills in environments without internet access.
- Prototyping dashboard UI components that require structured weather data like humidity and wind speed.
- Generating consistent 1-7 day forecasts for specific cities during integration testing.
How Mock Weather Skill Works
- The AI agent or user invokes the script by providing a city name and an optional forecast parameter.
- The system utilizes a deterministic algorithm that uses the city name and current date as a seed to ensure consistent results within a 24-hour window.
- The skill calculates simulated values for weather conditions (e.g., Sunny, Rain), temperature ranges, humidity percentages, and wind force.
- The resulting data is formatted into a readable output, allowing the Openclaw Skills agent to present the information to the end-user.
Mock Weather Skill Setup
To use this skill within your environment, ensure you have the script available in your path and run it via the command line:
# Get current weather for a city
python3 scripts/mock_weather.py Beijing
# Generate a multi-day forecast (1-7 days)
python3 scripts/mock_weather.py London --forecast 5
Mock Weather Skill Data Schema & Taxonomy
The Mock Weather Skill organizes its output into a structured format containing the following metadata:
| Field | Description |
|---|---|
| Weather | The simulated atmospheric condition (e.g., Sunny, Cloudy, Rain, Snow) |
| Temperature | High and Low values provided in Celsius (°C) |
| Humidity | The relative humidity level expressed as a percentage (%) |
| Wind | A combination of wind direction and Beaufort scale intensity |
All data generated by this tool in the context of Openclaw Skills should be marked as simulated for transparency.
Mock Weather Skill Advanced Features
- Deterministic generation ensures that the same city produces the same weather results for all Openclaw Skills users on the same day.
- Full support for bilingual input, accepting both Chinese and English city names.
- Configurable forecast range allows for testing agent responses across a 7-day period.
- Lightweight implementation with no external dependencies on climate service providers.
SKILL.md
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