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To create an AI agent skill, you need structured guidance on defining modular components, organizing scripts and references, and applying naming conventions to ensure context efficiency and progressive disclosure.

Refactoring AI skills for context efficiency involves auditing the current structure, removing outdated content, and reorganizing files to ensure progressive disclosure of information to the agent.

Progressive disclosure in agent skill development works by structuring modular assets and references so that the AI only loads specific information when contextually required, optimizing overall token usage.

Yes, you can use this skill auditing approach to validate the structure and organization of assets for specific workflows like cloud deployment, ensuring files and references meet established specifications.

No specific dependencies are required to start building modular AI skills; the process relies on internal scripts and reference components to guide the creation and editing workflow.

Modular skill development for AI coding assistants separates scripts, references, and assets, which improves maintainability, enables efficient context usage, and simplifies content auditing.