overtraining-check

Name: overtraining-check
Availability: InStock
Author: alvarolaraff

Compute ACWR, monotony, and strain from daily loads to detect overtraining risk.

Updated Apr 12, 2026

Search Tags:#coaching #training-load #strain #athlete #acwr #overtraining #monotony

Ready to run

npx skills add https://github.com/AlvaroLaraFF/strava-coach --skill overtraining-check

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: overtraining-check
Source: https://github.com/AlvaroLaraFF/strava-coach/tree/main/.claude/skills/overtraining-check
Command: npx skills add https://github.com/AlvaroLaraFF/strava-coach --skill overtraining-check

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Detect overtraining risk using ACWR, monotony, and strain derived from recent training loads to guide coaching decisions.

Core Features & Use Cases

Three-metric overtraining screen based on Foster's model: ACWR, monotony, and strain.
Pre-flight: read athlete snapshot to seed physiologic inputs (hr_max, hr_rest, ftp) and adapt calculations.
Post-run: persist a qualitative coaching observation to memory to inform future decisions.

Quick Start

Ask it to evaluate your recent training data and return a red/yellow/green verdict with a concrete recovery recommendation.

Frequently Asked Questions about overtraining-check

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I check overtraining risk using ACWR and training strain?▼

Overtraining risk is checked by computing ACWR, monotony, and strain from daily loads over a 28- to 35-day window, returning a red, yellow, or green verdict with a concrete recovery recommendation for endurance athletes.

What is the ACWR training load calculation process for endurance athletes?▼

The ACWR calculation evaluates recent training loads by comparing acute and chronic workload, while also calculating monotony and strain based on Foster's model to decide whether to back off or continue training as planned.

Can I use training monotony and strain metrics for running, cycling, and swimming?▼

Yes, the three-metric overtraining screen applies to endurance athletes across running, cycling, and swimming by deriving monotony and strain from recent daily loads to guide coaching decisions.

Do I need athlete profile inputs like hr_max and ftp to evaluate overtraining?▼

Athlete profile inputs are optional; the calculation pre-reads the athlete snapshot to seed physiologic inputs like hr_max, hr_rest, and ftp to adapt calculations, but it relies primarily on local database data of daily loads.

How do I interpret the overtraining risk verdict and recovery recommendation?▼

The skill outputs a JSON payload containing a red, yellow, or green verdict alongside the computed metrics and a specific recommendation on whether to back off or continue as planned, followed by a memory update step.