What kind of data can the Training Log Analyzer process?

The skill can analyze a wide range of training data including sets, reps, weight, cardio duration, intensity metrics, and subjective recovery scores.

How does the skill identify a training plateau?

It looks for statistical stagnation in performance metrics over a specific time horizon and suggests changes in volume or intensity to stimulate new growth.

Can I use this for specific sports like powerlifting or running?

Yes, it is designed as a domain-agnostic performance analyst that adapts its recommendations based on the specific sport data you provide.

How does it help prevent injuries?

It monitors training volume spikes and lack of rest days to flag potential overtraining indicators before they lead to physical injury.

Training Log Analyzer

Name: Training Log Analyzer
Author: Microck

byMicrock

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Ciencia de Datos y ML

Analyzes athletic performance data and workout logs to identify trends, recovery needs, and injury risks.

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The Training Log Analyzer transforms Claude into a digital sports scientist designed to extract actionable insights from fitness data. By evaluating workout logs over time, the skill identifies performance plateaus, calculates recovery requirements, and forecasts peak performance windows. It is an essential tool for athletes and coaches looking to make data-driven training adjustments and mitigate injury risks through systematic analysis of training volume and intensity.

Características Principales

81 GitHub stars
Data-driven plateau identification and training pivots
Rest and recovery requirement analysis
Comprehensive performance trend and improvement tracking
Peak performance window and taper forecasting
Early-warning injury risk assessment based on training load

Casos de Uso

Generating a structured summary of recovery metrics before a competition
Evaluating strength training logs to overcome a stalled bench press or squat
Analyzing running mileage and heart rate data to prevent overtraining

Acerca de

Características Principales

81 GitHub stars
Data-driven plateau identification and training pivots
Rest and recovery requirement analysis
Comprehensive performance trend and improvement tracking
Peak performance window and taper forecasting
Early-warning injury risk assessment based on training load

Casos de Uso

Generating a structured summary of recovery metrics before a competition
Evaluating strength training logs to overcome a stalled bench press or squat
Analyzing running mileage and heart rate data to prevent overtraining