skill-creator

The best way to structure an AI skill is using a modular anatomy with a root SKILL.md file and optional resource directories like scripts/, references/, and assets/ to ensure efficient agent discoverability. This organization enforces conciseness and progressive disclosure.

To create an AI skill, follow a structured development workflow: understand the skill requirements, organize content into SKILL.md and supporting directories, and iteratively refine the prompt engineering and scripts. This ensures the final skill is modular and efficient.

To build a modular AI skill, you need a core SKILL.md file for documentation and can include optional directories such as scripts for automation, references for documentation, and assets for static resources. This structure separates logic from content.

AI agents struggle with custom prompt engineering workflows when skills lack modular structure, conciseness, and progressive disclosure. Enforcing best practices in content organization within SKILL.md and resource directories resolves these discoverability issues.

Yes, you can use this skill creation workflow to manage cloud deployment scripts by placing them in the scripts/ directory and documenting cloud-specific configurations in the references/ or SKILL.md file for AI agents to easily parse.

You should avoid using a single SKILL.md file for complex AI development when content becomes too lengthy, violating progressive disclosure. Instead, split logic into scripts/ and detailed documentation into references/ to maintain skill efficiency.