Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Version 1.2.2 - Updated conversational examples to clarify that city/country context should be taken from the session, not USER.md. - Minor edits for clarity and consistency in documentation wording. - No functional or code changes detected.
What This Skill Does
Runs advanced weather queries using the openmeteo CLI against the free OpenMeteo API. Covers current conditions, forecasts up to 16 days, historical data back to 1940, and fine-grained variable selection including pressure, dew point, snow depth, and UV index. No API key or account required.
Provides historical data back to 1940 and fine-grained variable control without requiring any API key or account signup, which most weather APIs do not offer for free.
When to use it
- Checking how much rain fell in a city during a specific past month
- Getting hourly precipitation probability to decide whether to carry an umbrella
- Fetching weekend forecast with only min/max temp and condition code
- Querying sea-level pressure and dew point for a sailing trip
- Retrieving historical snowfall totals for a date range in the 1980s
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: How much did it rain in Paris last January?
- 1Identifies the request as a historical precipitation query
- 2Constructs a history command with --start-date=2025-01-01 and --end-date=2025-01-31 for Paris
- 3Adds --daily-params=precipitation_sum,rain_sum to limit output to relevant variables
- 4Runs: openmeteo history --city="Paris" --start-date=2025-01-01 --end-date=2025-01-31 --daily-params=precipitation_sum,rain_sum --llm
- 5Summarizes total rainfall and highlights the wettest days in plain language
Paris received 47mm of rain in January 2025, with the heaviest rainfall on January 12 (9mm) and January 19 (7mm).
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.