meta-structure-organizer

Organizing AI features into the correct structure uses a reusable framework that evaluates architecture decisions, applies trigger rules, and enforces frontmatter requirements to categorize concepts as Command, Skill, or Agent.

You need to organize AI feature architecture into specific component types during feature evaluations and design discussions, especially when seeking clear categorization and consistent design decisions in multi-team environments.

The best way to structure new AI features for consistent design decisions is providing a clear taxonomy that classifies concepts into Command, Skill, or Agent, ensuring a reusable framework for feature categorization and handoff.

No specific dependencies are required to evaluate architecture decisions; the framework operates independently to classify concepts into Command, Skill, or Agent structures based on trigger rules and frontmatter requirements.

To enforce consistent frontmatter requirements and trigger rules during feature categorization, you apply the framework's taxonomy to evaluate concepts and define workflows that dictate whether a feature becomes a Command, Skill, or Agent.

Yes, you can use the taxonomy to organize workflows for features that overlap, as the framework applies strict trigger rules and frontmatter requirements to force a clear categorization decision between Command, Skill, or Agent.