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strava-skill

Talk to your Strava data — ask questions about your activities, fitness trends, PRs, and training load using AI.

Why use this skill?

Use the Strava AI skill to track fitness trends, monitor training load, and get personalized workout suggestions directly from your activity data.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/nftechie/strava-skill
Or

What This Skill Does

The strava-skill allows your AI agent to interact directly with your athletic performance data. By integrating with Transition, the skill provides a bridge between your Strava activity history and AI-driven insights. It is designed to act as a personal coach, offering capabilities to analyze fitness trends, summarize historical performance, track training load, and even generate structured workouts on the fly. Whether you are an endurance athlete monitoring your CTL/ATL/TSB metrics or a casual runner looking for a randomized training plan, this skill parses complex activity data into actionable human-readable insights.

Installation

To begin, ensure you have the OpenClaw environment properly configured. You can install the skill by running the following command in your terminal: clawhub install openclaw/skills/skills/nftechie/strava-skill. Once installed, you must register for an account at Transition and generate an API key via their settings dashboard. You are required to set this key as an environment variable in your system: export TRANSITION_API_KEY="tr_live_xxxxxxxxxxxxxxxxxxxxx". This key authenticates your requests to the Transition API, allowing the agent to securely access your specific Strava telemetry.

Use Cases

This skill is highly effective for athletes who want to offload data analysis to an AI. Key use cases include: 1. Post-workout analysis: Ask the AI to summarize how a recent long run compared to previous sessions to determine if you are overtraining. 2. Performance tracking: Use the PMC endpoint to monitor your fatigue and fitness levels over a 90-day window. 3. Training planning: Use the wod feature to generate tailored workout suggestions based on your preferred sport and available time. 4. Goal setting: Retrieve personal records and performance stats to understand where your threshold paces currently sit and identify areas for improvement.

Example Prompts

  1. "How has my training load changed over the last two weeks, and should I be concerned about fatigue?"
  2. "Generate a 60-minute cycling workout that focuses on endurance intervals."
  3. "What does my current performance management chart tell me about my readiness for an upcoming race?"

Tips & Limitations

Note that the skill is subject to rate limits based on your subscription tier; free users are limited to 3 AI-driven chats per day. Ensure your Strava data is synced regularly with Transition for the most accurate insights. Because this skill interacts with external fitness APIs, ensure you review your privacy settings in Strava to confirm which data points are shared with third-party applications.

Metadata

Author@nftechie
Stars1335
Views0
Updated2026-02-23
View Author Profile
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-nftechie-strava-skill": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags(AI)

#fitness#health#sports#coaching#data-analysis
Safety Score: 5/5

Flags: external-api