Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Fixed metadata: declare required env vars and config paths per ClawHub schema
What This Skill Does
Fetches cycling workout data from the Peloton API using only Python stdlib. Pulls weekly stats including rides, duration, calories, output, power, resistance, and cadence, plus a recent rides table with instructor info.
Zero external dependencies means no virtual environment or package installs — just Python and your credentials.
When to use it
- Check weekly cycling progress before a Monday review
- Compare power output across rides this week
- See which instructors you rode with recently
- Track total calories burned over the last 7 days
- Get a quick workout summary without opening the Peloton app
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Show me my Peloton stats for this week
- 1Reads Peloton credentials from auth-profiles.json
- 2Authenticates against api.onepeloton.com
- 3Fetches cycling workouts from the last 7 days
- 4Aggregates totals and averages across all rides
- 5Formats results as a markdown report with a recent rides table
Markdown summary showing 4 rides, 210 min, 1,840 cal, 320 kJ output, avg 185W, 52% resistance, 84 RPM, with per-ride breakdown by date, class, and instructor
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.