skill-creator

AI skill authoring involves creating structured SKILL.md files that guide model execution. Progressive disclosure structures instructions hierarchically, revealing details only when needed to ensure discoverability and prevent context overload.

To write a SKILL.md file, follow a structured authoring decision tree to define frontmatter, content, and structure. Adhering to open standards ensures the AI skill is discoverable, executable, and robust across different environments.

Anti-rationalization patterns are constraints embedded within AI skills to prevent models from skipping steps or hallucinating justifications. They enforce disciplined execution by requiring rigorous verification and adherence to detailed checklists.

You do not need specific external developer tools to create AI skills, as the process relies on authoring SKILL.md files using standard text formats. The primary requirements are understanding prompt engineering and following structured documentation best practices.

The best way to verify AI skills is by applying detailed evaluation methodologies and checklists. This process ensures frontmatter, content, and structure meet open standards, validating that the skill is robust and ready for submission.

AI skills fail to execute reliably when they lack structured authoring, progressive disclosure, or anti-rationalization patterns. Enforcing best practices for frontmatter and content structure ensures disciplined execution and robust performance.