skill-creator

Progressive disclosure in AI skill development is a design principle that structures SKILL.md content and resource organization to reveal complexity only when needed. It guides users through conciseness, setting degrees of freedom, and organizing assets efficiently.

To structure an AI skill for an internal API, you organize components by placing instructions in SKILL.md, executable logic in the scripts directory, and API documentation in the references directory. This ensures the AI agent can efficiently interact with the target API.

The best way to write a SKILL.md file for workflow automation is to follow design principles of conciseness and setting degrees of freedom. It should clearly outline the core task, use cases, and step-by-step processes to guide the AI agent effectively.

You need intermediate implementation depth to create and package AI skills, meaning some technical familiarity is required. The process involves initializing the skill, writing structured documentation, and validating components like scripts and references.

Yes, you can use prompt engineering to improve AI agent tooling by applying structured design principles. This involves organizing resources progressively and writing concise SKILL.md files to constrain and guide the agent's behavior accurately.

You should not use a structured skill anatomy when your AI agent task requires minimal documentation or lacks reusable logic. If the task does not benefit from organized scripts, references, and progressive disclosure, a full skill structure may be unnecessary overhead.