generate-skill

To create a portable AI skill, you generate a `SKILL.md` file using a portable core + explicit adapter mental model, ensuring the Markdown instructions and YAML frontmatter remain framework-independent while vendor-specific configurations go into separate adapters.

Discovery-optimized descriptions for AI skills require crafting precise `name` and `description` fields in the YAML frontmatter, ensuring the intent and trigger conditions are clearly defined for accurate AI auto-discovery and capability matching.

The portable core + adapter model separates framework-independent Markdown instructions from vendor-specific adapter configurations, allowing an AI skill to maintain portability across different execution environments while supporting targeted integrations.

Yes, you can automate the generation of a `SKILL.md` file including its YAML frontmatter by guiding the tool through defining your intent, deriving a name, and structuring the instructions for tasks like security vulnerability analysis.

Yes, the skill generation process supports structured naming conventions and requirement gathering, walking you through defining the intent and deriving a compliant name before outputting the portable core and adapter configurations.

You should use vendor-specific adapter configurations when targeting a particular platform's execution environment, keeping the portable core reserved for framework-independent instructions to maintain maximum portability.