peloton-statsFetch and report Peloton cycling workout statistics. Use when the user wants to see their Peloton workout data, weekly cycling stats, ride history, or perfor...
Install via ClawdBot CLI:
clawdbot install niemesrw/peloton-statsFetch weekly cycling stats directly from the Peloton API. Zero dependencies — uses only Python stdlib.
Store your Peloton credentials securely using OpenClaw's credential manager:
openclaw config set auth.profiles.peloton:default.type api_key
openclaw config set auth.profiles.peloton:default.provider peloton
openclaw config set auth.profiles.peloton:default.username "your-email@example.com"
openclaw config set auth.profiles.peloton:default.password "your-password"Or edit ~/.openclaw/agents/main/agent/auth-profiles.json directly:
{
"profiles": {
"peloton:default": {
"type": "api_key",
"provider": "peloton",
"username": "your-email@example.com",
"password": "your-password"
}
}
}python3 ~/.openclaw/skills/peloton-stats/scripts/fetch_stats.pyOutputs markdown with:
| Metric | Description |
|--------|-------------|
| Total Rides | Number of cycling workouts in last 7 days |
| Duration | Total minutes ridden |
| Calories | Total calories burned |
| Output | Total energy in kilojoules (kJ) |
| Avg Power | Average watts across all rides |
| Avg Resistance | Average resistance % |
| Avg Cadence | Average RPM |
api.onepeloton.comGenerated Mar 1, 2026
Individuals use this skill to monitor their weekly cycling performance, track progress toward fitness goals, and maintain motivation by reviewing metrics like calories burned and average power. It helps users stay accountable and adjust their workout intensity based on data trends.
Companies integrate this skill into employee wellness initiatives to encourage physical activity, reduce healthcare costs, and boost productivity. HR teams can aggregate anonymized data to assess program effectiveness and offer incentives based on weekly cycling achievements.
Personal trainers and cycling coaches use this skill to remotely monitor clients' Peloton workouts, analyze performance metrics like resistance and cadence, and provide tailored feedback. It enables data-driven coaching without requiring in-person sessions.
Developers embed this skill into health and fitness applications to automatically pull Peloton cycling data, creating comprehensive activity dashboards. Users get a unified view of their workouts alongside other health metrics like sleep or nutrition.
Researchers and sports scientists utilize this skill to collect anonymized cycling data for studies on exercise physiology, performance trends, or behavioral patterns. It provides a direct API access point for analyzing metrics like output and duration over time.
Offer a premium service where users pay a monthly fee to access enhanced Peloton analytics, such as historical trend visualizations, personalized insights, and goal-setting features. Revenue is generated through tiered subscription plans with advanced reporting capabilities.
License this skill to corporate wellness providers, gym chains, or health insurers who integrate it into their existing platforms. Charge based on the number of users or through annual licensing agreements, providing scalable data-fetching capabilities for large groups.
Develop a mobile app that uses this skill to deliver basic Peloton stats for free, with in-app purchases or ads unlocking advanced features like comparative analytics, social sharing, or integration with other fitness devices. Monetize through ads and premium upgrades.
💬 Integration Tip
Ensure secure credential storage via OpenClaw's auth-profiles.json and verify the Peloton API endpoint availability before deployment to avoid authentication errors.
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