Skill Name

To define a reusable AI skill using YAML frontmatter, you add a SKILL.md file to your project's Skill directory with the required name and description metadata, plus optional version and when_to_use fields for discovery and management.

Frontmatter-based skill discovery is a mechanism where YAML metadata in a SKILL.md file exposes a modular AI skill's name and description, allowing workflows to automatically find, load, and activate reusable capabilities across teams.

You modularize task automation instructions by writing the operational steps in the body of a SKILL.md file, which gets loaded into the context upon activation to provide immediate, standardized execution flows for team reuse.

Yes, you can chain reusable skills together in a single workflow by defining them as modular components, using optional dependencies in the SKILL.md frontmatter to link capabilities across different automated tasks.

You do not need to include version and when_to_use fields in your SKILL.md frontmatter, as they are optional metadata used only for facilitating easier skill management and version configuration.

The best way to standardize AI skill definitions across multiple teams is to use a SKILL.md template with consistent YAML frontmatter for discovery and a structured body for operational instructions, ensuring uniform capability loading and execution.