category-manager

To build a new JARVIS category, define its layer, assign a category number, and set up the full directory structure including CLAUDE.md and settings.json configurations to ensure ecosystem compliance.

JARVIS category validation runs a comprehensive checklist to ensure categories meet structural, configuration, skill, and plugin requirements, verifying settings.json format and CLAUDE.md structure for ongoing compliance.

Yes, you can audit and improve existing JARVIS categories by facilitating a self-improvement cycle that updates documentation, refines configurations, and resolves settings.json or CLAUDE.md compliance issues.

Integrating a new AI capability requires defining the category layer, establishing the directory structure, and formatting settings.json correctly to ensure the primary skill meets JARVIS ecosystem standards from setup to maintenance.

JARVIS category compliance checks fail when the CLAUDE.md structure is incorrect, settings.json format is invalid, or required structural, skill, and plugin requirements are missing from the directory configuration.

The best way to manage the JARVIS category lifecycle is to use an automated workflow for creation, validation, and self-improvement, ensuring consistent structure and effectiveness across the AI ecosystem.