A powerful AI integration for Fitbit that provides deep insights into your physical activity, sleep patterns, and heart rate data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install fitbit-insights
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-insights 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 Fitness Insights?
The Fitbit skill for Openclaw Skills allows developers and users to bridge the gap between their personal health data and AI agents. By integrating with the Fitbit Web API, this skill enables an AI agent to query, analyze, and interpret complex fitness metrics like heart rate zones, sleep stages, and workout consistency. It transforms raw biometric numbers into actionable advice and conversational health summaries.
Whether you are looking to automate a health dashboard or simply want to ask your AI assistant how well you recovered overnight, this skill provides the necessary tooling to fetch and process Fitbit data securely. It features built-in OAuth token management and automatic refreshes to ensure seamless, long-term connectivity with the Fitbit ecosystem within the Openclaw Skills framework.
Fitbit Fitness Insights Use Cases
- Querying daily step counts and active minutes via conversational AI.
- Analyzing sleep quality and efficiency trends over specific date ranges.
- Generating weekly fitness reports to track progress against personal goals.
- Correlating workout intensity with heart rate zone data for performance reviews.
- Checking for specific logged exercise sessions and calorie expenditures.
How Fitbit Fitness Insights Works
- The agent identifies a user request related to fitness, health, or activity data.
- It triggers the relevant script command (e.g., daily, sleep, or weekly) using Openclaw Skills logic.
- The skill interacts with the Fitbit Web API using a secure OAuth access token.
- Raw JSON data is returned and processed by the AI to identify trends, goals, and anomalies.
- The agent delivers a human-readable summary or insight based on the retrieved metrics.
Fitbit Fitness Insights Setup
To get started with the Fitbit integration for Openclaw Skills, you need a Fitbit OAuth token. Follow these steps:
- Obtain your Fitbit OAuth credentials from the Fitbit Developer Portal.
- Configure your access token in
/root/clawd/fitbit-config.json. - Verify your profile connection using the CLI:
FITBIT_ACCESS_TOKEN="your_token" python3 scripts/fitbit_api.py profile
- For manual token refreshes if needed, use:
python3 scripts/refresh_token.py force
Fitbit Fitness Insights Data Schema & Taxonomy
The skill organizes fitness data into structured metrics for easy AI consumption. Key data points include:
| Category | Metrics Tracked |
|---|---|
| Activity | Steps, distance, calories, floors, active minutes (sedentary to very active) |
| Heart Rate | Resting heart rate, time spent in specific heart rate zones |
| Sleep | Duration, efficiency, start/end times, and granular sleep stages |
| Workouts | Activity name, duration, calories burned, and distance per log |
| Summaries | 7-day rolling averages and weekly goal comparisons |
Fitbit Fitness Insights Advanced Features
- Automated token refreshing every 8 hours via local configuration files.
- Multi-metric correlation such as comparing sleep quality to previous day activity levels.
- Support for specific date range queries for long-term health trend analysis.
- Conversational Q&A capabilities for complex health inquiries using Openclaw Skills.
- Environment variable overrides for manual developer testing and debugging.
SKILL.md
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