A Python-powered integration to retrieve surf forecasts and spot conditions from Surfline's public endpoints without requiring a login.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install surfline
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install surfline using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
This skill provides a streamlined interface for accessing Surfline data through public endpoints. It allows users and agents to search for specific surf spot IDs, retrieve detailed forecast reports in text or JSON format, and maintain a list of favorite spots for quick summaries. As part of the Openclaw Skills ecosystem, it enables AI agents to provide real-time surf insights without requiring user authentication, cookies, or complex session management.
By leveraging the scripts provided, developers can integrate high-quality swell, wind, and tide data into their workflows. The skill is designed to be gentle on endpoints with built-in caching and utilizes stable spot IDs for consistent reporting across different sessions.
Use the search script to find the ID for your local break:
python3 scripts/surfline_search.py "Cardiff Reef"
Fetch the latest conditions for a specific spot ID:
python3 scripts/surfline_report.py <spotId> --text
To track multiple spots, create a configuration file at ~/.config/surfline/favorites.json based on the provided example, then run:
python3 scripts/surfline_favorites.py
| Element | Type | Description |
|---|---|---|
| favorites.json | Config | A JSON file located in ~/.config/surfline/ storing favorite spot IDs and names. |
| spotId | String | The unique identifier used by Surfline public endpoints to index surf locations. |
| Output Formats | Flag | Supports --text for CLI readability and --json for data serialization. |
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