What is a Collaboration Health Check in Claude Code?

It is a structured review process where Claude assesses its partnership with the user to identify improvements in communication, trust, and workflow efficiency.

Where are the health check results saved?

Insights, scores, and action items are automatically documented in a file named HEALTH_CHECK_LOG.md within your project repository.

How does this skill improve my coding workflow?

It helps eliminate recurring friction points, adjusts Claude's verbosity to your preference, and ensures that development frameworks are helping rather than hindering progress.

Can I customize how often the health check occurs?

Yes, the cadence is managed via a config.json file and can be set to trigger every 14, 21, or 30 sessions depending on your project's intensity.

Collaboration Health Check

Name: Collaboration Health Check
Author: jkraybill

byjkraybill

Herramientas de Colaboración

Conducts structured periodic reviews to proactively optimize communication, trust calibration, and workflow efficiency between Claude and the user.

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The Collaboration Health Check skill is a specialized diagnostic tool designed to maintain high-quality partnerships between users and Claude. It guides the AI through a structured four-dimension interview—assessing general collaboration quality, communication patterns, framework effectiveness, and recurring behavioral patterns. By identifying friction points early and documenting them in a local health log, the skill allows for real-time adjustments to trust levels, response verbosity, and workflow shortcuts, ensuring a seamless and productive long-term development environment.

Características Principales

Automated feedback logging in HEALTH_CHECK_LOG.md
Structured 4-step interview process for partnership assessment
Actionable synthesis and immediate framework documentation updates
Real-time trust calibration and communication pacing adjustments
Configurable review cadences based on project intensity
0 GitHub stars

Casos de Uso

Onboarding users to complex development frameworks to ensure smooth collaboration
Managing long-term software projects where communication alignment is critical
Optimizing high-intensity coding sessions by removing recurring friction points

Acerca de

Características Principales

Automated feedback logging in HEALTH_CHECK_LOG.md
Structured 4-step interview process for partnership assessment
Actionable synthesis and immediate framework documentation updates
Real-time trust calibration and communication pacing adjustments
Configurable review cadences based on project intensity
0 GitHub stars

Casos de Uso

Onboarding users to complex development frameworks to ensure smooth collaboration
Managing long-term software projects where communication alignment is critical
Optimizing high-intensity coding sessions by removing recurring friction points