A comprehensive integration to sync WHOOP biometric data with AI agents for automated recovery reporting and physiological-aware productivity coaching.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install whoop-integration
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 whoop-integration 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 WHOOP Fitness Tracker Integration?
The WHOOP Integration allows your AI agent to interface directly with the WHOOP developer platform to retrieve high-fidelity biometric data including recovery scores, sleep performance, and physiological strain. By utilizing the Openclaw Skills framework, developers can build agents that are contextually aware of a user's physical readiness, enabling a personalized assistant experience that knows when to push for performance and when to prioritize rest.
This skill automates the complex OAuth 2.0 handshake and token rotation cycles required by the WHOOP API, providing a seamless stream of data including HRV, resting heart rate, and sleep stage breakdowns. It bridges the gap between wearable technology and autonomous agents, making health data actionable within your existing workflows.
WHOOP Fitness Tracker Integration Use Cases
- Automated morning recovery reports delivered to communication channels like Telegram.
- Dynamic adjustment of AI agent task recommendations based on real-time recovery scores.
- Long-term trend analysis for HRV, resting heart rate, and sleep efficiency to identify burnout patterns.
- Behavioral coaching triggers that suggest lighter workloads when recovery falls below 34%.
How WHOOP Fitness Tracker Integration Works
- The skill authenticates with the WHOOP API using OAuth 2.0 credentials provided via environment variables.
- It manages a secure local token store, automatically handling rotation when the access token is within one hour of expiration.
- The agent polls the V2 endpoints to fetch the latest sleep, recovery, and workout records.
- Data is parsed to calculate metrics such as sleep performance percentages and recovery-based color zones (Green, Yellow, Red).
- The skill provides structured outputs that allow the AI agent to adjust its tone and task complexity based on the user's current physiological state.
WHOOP Fitness Tracker Integration Setup
To get started with this skill within the Openclaw Skills ecosystem, you must configure your developer credentials:
# Set your WHOOP Developer credentials
export WHOOP_CLIENT_ID="your_client_id_here"
export WHOOP_CLIENT_SECRET="your_client_secret_here"
Ensure that your redirect URIs are correctly configured in the WHOOP Developer Dashboard to allow for successful OAuth authentication. The skill will automatically manage tokens in the ~/.openclaw/whoop_tokens.json file.
WHOOP Fitness Tracker Integration Data Schema & Taxonomy
The skill organizes its authentication and biometric data following a structured schema:
| Object | Fields | Description |
|---|---|---|
| Tokens | access_token, refresh_token, expires_at | Manages API access and automatic rotation logic. |
| Sleep | sleep_performance_percentage, respiratory_rate, stage_summary | Detailed breakdown of sleep quality and cycles. |
| Recovery | recovery_score, resting_heart_rate, hrv_rmssd_milli | Core metrics determining daily physical readiness. |
| Cycles | strain, max_heart_rate, average_heart_rate | Cardiovascular load data for specific time periods. |
WHOOP Fitness Tracker Integration Advanced Features
- Adaptive AI Behavior: Automatically modifies agent communication style and task ambition based on recovery thresholds (>80% for ambitious tasks, <34% for minimal complexity).
- Automated Morning Reports: Built-in support for formatted Telegram summaries including recovery recommendations and sleep efficiency statistics.
- Historical Trend Analysis: Supports deep-dive queries using ISO 8601 timestamps to track health improvements or declines over custom periods.
- V2 API Compliance: Specifically engineered to use WHOOP V2 endpoints for increased reliability and data depth.
SKILL.md
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