skill-creator

To structure an AI skill for progressive disclosure, organize content into a main SKILL.md file alongside scripts, references, and assets directories. This anatomy ensures the AI retrieves only necessary information, maintaining conciseness and token efficiency.

The AI skill creation process involves understanding the skill's purpose, defining its structure, packaging the content correctly, and iterating. Following this step-by-step guide ensures the final skill is discoverable, adaptable, and maintainable for modular AI capabilities.

Best practices for building token-efficient AI skills include maintaining conciseness, applying progressive disclosure to minimize context window usage, and defining appropriate degrees of freedom to guide agentic flow without unnecessary token consumption.

Yes, you can use this approach to create internal knowledge base skills by defining the skill's purpose, structuring the documentation, and packaging it correctly. It guides developers through building modular AI capabilities tailored for company-specific applications.

The appropriate degree of freedom when designing an agentic flow balances strict guidance with AI autonomy, ensuring the skill remains adaptable. This principle prevents overly rigid instructions while maintaining token efficiency within the skill anatomy.