What data does the skill require?

The skill needs your current plan, a record of completed vs. missed workouts, and your available training days or constraints.

How does the Adherence Coach handle missed sessions?

The skill identifies missed sessions and proposes a reshuffled plan that prioritizes habit re-entry, ensuring you get back on track without overwhelming volume.

Does it provide motivational feedback?

Yes, it generates a 'CoachMessage' alongside reshuffle suggestions to provide supportive nudges and keep you motivated.

Can this skill help prevent training injuries?

Yes, it includes safety guardrails that limit catch-up sessions and will suggest professional consultation instead of training if lapses are due to pain.

When should I use the Adherence Coach skill?

It is best used for weekly digests every Sunday or whenever you feel you have fallen behind on your specific training goals.

Adherence Coach

Name: Adherence Coach
Author: nadavyigal

bynadavyigal

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Productividad y Flujo de Trabajo

Optimizes training schedules by identifying missed sessions and proposing intelligent plan reshuffles to maintain habit consistency.

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The Adherence Coach skill is designed to keep users on track with their training plans by acting as an intelligent mentor within the Codex environment. It analyzes session data to detect inconsistencies, generates weekly progress digests, and suggests balanced plan adjustments that prioritize habit re-entry over dangerous 'catch-up' volume. By combining data-driven reshuffling with supportive motivational messaging, it helps users overcome setbacks while maintaining strict safety guardrails to prevent overtraining and injury.

Características Principales

Automated detection of missed sessions and consistency gaps
Intelligent plan reshuffling based on user constraints and availability
Motivational messaging to encourage habit re-entry and engagement
Safety-first logic that limits catch-up intensity and volume
Automated injury flags that suggest professional consultation over training
1 GitHub stars

Casos de Uso

Requesting a plan reshuffle after missing several days due to travel or illness
Generating a Sunday weekly digest to review adherence and set the upcoming schedule
Getting back on track with a conservative re-entry plan after a long training lapse

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Características Principales

Automated detection of missed sessions and consistency gaps
Intelligent plan reshuffling based on user constraints and availability
Motivational messaging to encourage habit re-entry and engagement
Safety-first logic that limits catch-up intensity and volume
Automated injury flags that suggest professional consultation over training
1 GitHub stars

Casos de Uso

Requesting a plan reshuffle after missing several days due to travel or illness
Generating a Sunday weekly digest to review adherence and set the upcoming schedule
Getting back on track with a conservative re-entry plan after a long training lapse