An AI-powered endurance cycling coach that leverages Intervals.icu data to provide personalized training analysis and workout planning.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ftpilot
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 ftpilot 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 FTPilot?
FTPilot is a sophisticated AI coaching agent designed for endurance cyclists who rely on power-based training metrics. By integrating directly with Intervals.icu data, this skill acts as a digital sport scientist, capable of analyzing complex physiological markers such as Chronic Training Load (CTL), Acute Training Load (ATL), and Heart Rate Variability (HRV). It provides cyclists with a structured, data-driven approach to fitness, ensuring that every training recommendation is backed by recent performance trends.
The core value of this Openclaw Skills integration lies in its strict adherence to professional coaching principles. It doesn't just suggest workouts; it evaluates recovery status, fatigue levels, and aerobic efficiency to prevent overtraining. Whether you are looking to improve your FTP or analyze heart rate decoupling from your last ride, FTPilot provides the technical depth required for high-level athletic progression.
FTPilot Use Cases
- Analyzing recent ride files to check for heart rate decoupling and aerobic efficiency.
- Determining optimal training intensity based on current fitness status (CTL/ATL/Form).
- Generating structured workout files in Intervals.icu format for bike computers.
- Monitoring recovery through HRV and sleep data to decide if high-intensity training is safe.
- Planning a weekly training block that balances Sweet Spot, VO2max, and recovery rides.
How FTPilot Works
- The agent fetches athlete profile data including FTP, power zones, and heart rate zones using the athlete tool.
- It retrieves wellness metrics like HRV, sleep, and fatigue to assess the user's recovery state.
- Recent activity history is analyzed to calculate current Form and identify recent high-intensity clusters.
- The skill applies a strict priority logic where recovery status overrides all training goals.
- If the athlete is deemed trainable, the agent selects an appropriate workout type and generates a structured description using specific syntax.
- The final output provides a comprehensive training assessment, a specific recommendation, and a copy-paste ready workout format.
FTPilot Setup
To enable FTPilot within Openclaw Skills, you need to configure your environment with your Intervals.icu credentials.
# Set your environment variables
export INTERVALS_API_KEY="your_api_key"
export INTERVALS_ATHLETE_ID="your_athlete_id"
# Ensure npx is available to run the mcporter tools
npx ftpilot-mcp-command
FTPilot Data Schema & Taxonomy
The skill organizes cycling data into several key technical domains to ensure precise coaching:
| Data Category | Metrics Included |
|---|---|
| Athlete Profile | FTP, Power Zones (Z1-Z7), HR Zones, W', Pmax |
| Wellness | CTL, ATL, Form, HRV Trend, Sleep Duration, Subjective Fatigue |
| Power Analysis | Mean Maximal Power (MMP) Curves, Power vs HR Decoupling % |
| Calendar | Planned Events, Workout Compliance, Future Training Loads |
All generated workouts follow the Intervals.icu text-based format, utilizing specific syntax for duration (m, s, h) and intensity (% or watts).
FTPilot Advanced Features
- Multi-period power curve comparison to track fitness gains over months or years.
- Automated Risk Control: Hard-coded safety triggers that automatically downgrade workouts to recovery if HRV or fatigue metrics hit danger zones.
- Heart Rate Decoupling Analysis: Specialized logic to detect weakening aerobic bases if HR drift exceeds 10%.
- Precision Workout Generation: Supports complex repeat block syntax for intervals like 5x (4m 115% / 4m 50%).
- Integration with Openclaw Skills to function as a seamless part of a wider AI-driven productivity or health stack.
SKILL.md
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