AI coding tools are becoming increasingly complex, with a growing emphasis on using "skills" to manage instructions and resources effectively. Skills, part of the Agent Skills standard, function like folders that contain a definition markdown file and optional extras, such as scripts or templates. These skills are stored in a specific directory structure, allowing agents to access relevant information as needed without overwhelming their context. This progressive disclosure approach ensures that agents only load information pertinent to the task, helping maintain focus and efficiency. When determining the use of skills, commands, and rules, it’s essential to understand their distinctions. Rules are fixed and apply universally, while commands are explicit actions initiated by the user. Skills, on the other hand, are situational expertise that the agent retrieves when necessary. A clear breakdown helps clarify when to use each: rules handle repository requirements, commands are for repeatable workflows, and skills support task-specific needs. The decision tree provided in the article aids in categorizing instructions appropriately. The article emphasizes the importance of keeping instructions concise. Overloading agents with unnecessary information can detract from efficiency. Combining rules and skills can streamline workflows, reducing clutter while maintaining adaptability. For instance, a rule could dictate when to load a skill, keeping instructions clear and actionable. This method fosters a system where commands serve as ergonomic shortcuts to invoke relevant skills without burdening the agent with extraneous details. The text also touches on the evolving nature of AI tools and their context management capabilities. While some tools like Cursor allow for hierarchical rules, skills offer a more flexible, composable approach. Command structures should remain simple and memorable, while skills can be updated without requiring users to memorize new commands. This balance between usability and functionality is critical in optimizing AI interactions in coding environments.