What is the Bakken Norwegian Model?

It is a training philosophy focused on high-volume threshold training, emphasizing staying just below the lactate threshold to maximize aerobic gains while minimizing recovery time.

Does it support treadmill training?

Yes, it includes specific logic for 'gradient treadmill sessions' where heart rate is the primary metric for evaluating efficiency rather than pace.

Can this skill help prevent injuries?

Yes, it specifically monitors volume jumps and identifies when a runner is exceeding their intensity zones (Z3), providing warnings to prevent overtraining.

How do I use this skill with my running data?

You can provide FIT files to the plugin, which then uses 'npm run analyze' to generate JSON data for Claude to evaluate against Bakken principles.

What kind of feedback does it provide?

It provides a detailed breakdown of your session type, heart rate consistency, cardiac drift, and specific suggestions for your next 48 hours of training.

Bakken Run Coach

Name: Bakken Run Coach
Author: cbcruk

bycbcruk

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Data Science & ML

Analyzes fitness training data to provide professional running coaching feedback based on the Bakken Norwegian Model.

This skill transforms Claude into a specialized running coach that utilizes the Bakken Norwegian Model to analyze training sessions. By processing FIT file data, it evaluates heart rate zones, threshold consistency, and cardiac drift to ensure runners stay within optimal training windows. It is particularly valuable for marathoners seeking to improve performance while managing injury risks through disciplined threshold-centered workouts and gradient treadmill sessions. It provides honest, data-driven feedback to help runners build 'patience muscle' and maintain training volume without overtraining.

Key Features

01Automated FIT file analysis and session classification (Easy, Threshold, LSD, MP)

02Actionable next-step training suggestions and recovery guidance

03Heart rate zone tracking for LT1 and LT2 based on Bakken principles

04Automated overtraining warnings and 'Z3' threshold violation alerts

050 GitHub stars

06Detailed performance metrics including cardiac drift and consistency CV

Use Cases

01Post-workout analysis for marathon runners targeting sub-3:20/3:15 times

02Maintaining training discipline by identifying 'junk miles' and recovery needs

03Monitoring threshold training efficiency and cardiac drift over long distances

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add cbcruk/rog run

For use in Claude.ai and ChatGPT