A comprehensive integration for loading, analyzing, and tracking Strava fitness activities and athlete performance data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install strava
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 strava 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 Strava?
The Strava skill enables your AI agent to interface directly with the Strava API to retrieve a wide array of fitness data. This integration allows for the seamless extraction of activity logs, athlete statistics, and detailed workout metrics like distance, elevation, and heart rate.
Designed for developers looking to build health-oriented automation or personalized fitness dashboards, this skill for Openclaw Skills simplifies the process of interacting with OAuth-protected health data. It provides the tools necessary to monitor progress, analyze training trends, and manage athlete profiles programmatically.
Strava Use Cases
- Generating automated weekly fitness summaries and training reports.
- Filtering historical workout data to track progress toward specific distance or elevation goals.
- Integrating real-time fitness metrics into personal data analytics or health-monitoring applications.
- Programmatically retrieving athlete statistics to compare performance across different sport types.
How Strava Works
- The skill authenticates with the Strava API using an OAuth 2.0 access token provided in the configuration.
- When a request is made, the skill calls the appropriate Strava endpoint (e.g., athlete activities or stats).
- The API returns detailed JSON data containing specific workout metrics such as moving time, average speed, and sport type.
- For long-running sessions, the skill supports a refresh token workflow to maintain valid authentication without manual intervention.
- The output can be processed using standard CLI tools or analyzed directly by the AI agent within the Openclaw Skills environment.
Strava Setup
To get started with this skill, you must first create a Strava API application at https://www.strava.com/settings/api to obtain your Client ID and Client Secret.
Perform the OAuth exchange to get your initial tokens, then configure your credentials in ~/.clawdbot/clawdbot.json:
{
"skills": {
"entries": {
"strava": {
"enabled": true,
"env": {
"STRAVA_ACCESS_TOKEN": "your-access-token",
"STRAVA_REFRESH_TOKEN": "your-refresh-token",
"STRAVA_CLIENT_ID": "your-client-id",
"STRAVA_CLIENT_SECRET": "your-client-secret"
}
}
}
}
}
Alternatively, you can export the variables directly in your terminal:
export STRAVA_ACCESS_TOKEN="your-access-token"
export STRAVA_REFRESH_TOKEN="your-refresh-token"
Strava Data Schema & Taxonomy
The skill returns structured data based on the Strava API schema. Key fields in the activity objects include:
| Field | Description |
|---|---|
name |
Activity title |
distance |
Distance in meters |
moving_time |
Moving time in seconds |
total_elevation_gain |
Elevation gain in meters |
type |
Activity type (Run, Ride, Swim, etc.) |
start_date |
Start time in ISO 8601 format |
average_heartrate |
Average heart rate (if available) |
This schema allows Openclaw Skills to perform precise calculations and data transformations on your fitness history.
Strava Advanced Features
- Token refresh automation to handle the 6-hour expiration cycle of Strava access tokens.
- Granular date filtering using Unix timestamps for highly specific data extraction.
- Comprehensive athlete statistics retrieval, including all-time and seasonal performance totals.
- Advanced pagination support to navigate through large volumes of historical activity data.
SKILL.md
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