An advanced health integration for Openclaw Skills that automates Fitbit data retrieval, trend analysis, and personalized health reporting.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install fitbit-analytics
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 fitbit-analytics 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 Fitbit Analytics?
Fitbit Analytics is a specialized skill designed to bridge the gap between your wearable health data and automated workflows. By leveraging the Fitbit Web API, this Openclaw Skills integration allows developers to programmatically fetch granular metrics such as heart rate, sleep efficiency, and active zone minutes. It provides the infrastructure to transform raw fitness data into actionable insights through automated reports and historical trend analysis.
This skill is built for those who require more flexibility than the standard Fitbit mobile app. Whether you are building a personal health dashboard or integrating biometric data into a larger ecosystem, this skill provides the necessary wrappers and scripts to handle OAuth 2.0 authentication and complex data parsing with ease.
Fitbit Analytics Use Cases
- Generating automated morning health briefings sent directly to messaging platforms.
- Monitoring long-term cardiovascular trends by analyzing resting heart rate averages.
- Auditing sleep quality and efficiency over custom time periods for wellness optimization.
- Setting up inactivity alerts or daily goal notifications based on real-time step counts.
How Fitbit Analytics Works
- The skill initializes a FitbitClient using OAuth 2.0 credentials provided via environment variables.
- Commands are issued through the CLI or Python API to request specific data buckets like steps, sleep, or heart rate for a defined date range.
- The skill queries the Fitbit Web API endpoints and captures the response in structured JSON format.
- A built-in FitbitAnalyzer processes the data to calculate trends, such as comparing today's performance against a 7-day rolling average.
- The results are outputted in the user's preferred format (text, brief, or JSON) for display or further processing within Openclaw Skills.
Fitbit Analytics Setup
To use this integration with Openclaw Skills, you must first register an application at the Fitbit Developer portal to obtain your credentials.
# Set your Fitbit API credentials
export FITBIT_CLIENT_ID="your_client_id"
export FITBIT_CLIENT_SECRET="your_client_secret"
export FITBIT_ACCESS_TOKEN="your_access_token"
export FITBIT_REFRESH_TOKEN="your_refresh_token"
# Verify the installation by fetching a 7-day summary
python scripts/fitbit_api.py summary --days 7
Fitbit Analytics Data Schema & Taxonomy
The skill organizes health metrics into logical structures for easy consumption:
| Category | Metrics Tracked |
|---|---|
| Activity | Steps, Calories, Distance, Floors, Active Zone Minutes (AZM) |
| Cardiovascular | Resting HR, Average HR, Heart Rate Zones (Fat Burn, Cardio, Peak) |
| Sleep | Duration, Efficiency, Awake Minutes, Sleep Stages |
| Analysis | Daily vs 7-day average trends, Activity summaries |
Fitbit Analytics Advanced Features
- Seamless integration with Openclaw Skills gateway for automated cron job scheduling.
- Support for Active Zone Minutes (AZM) breakdown, including Fat Burn and Cardio zone durations.
- Threshold-based alerting system to notify users when specific health targets are missed.
- Multi-format CLI output enabling easy piping into other data processing tools.
SKILL.md
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