skill-creator

The best way to scaffold AI agent skills is using an init_skill.py generator to populate SKILL.md frontmatter and organize scripts, references, and assets. This ensures a repeatable structure and enforces naming conventions for project or user skill locations.

You validate SKILL.md frontmatter and naming conventions by running a quick validation script. This script checks YAML structure, naming constraints, and description limits to ensure agent compatibility and maintain self-contained skill directories.

An AI agent skill directory should include a SKILL.md file with frontmatter, example scripts, references, and assets. Organizational guidance advises keeping SKILL.md lean for efficient context usage while only including required components for the specific capability.

The skill scaffolding process requires the pyyaml dependency to handle YAML parsing for SKILL.md frontmatter. You need this Python library installed to properly generate templates and run the validation utilities for agent compatibility.

You need a template for creating AI agent skills to avoid reinventing directory structure, naming, and validation for every new capability. It provides a concise, repeatable process that ensures self-contained skills meet frontmatter requirements and description constraints.

You should add scripts when executable logic is needed and references when supporting documentation is required. Organizational guidance helps determine when to include these components or assets, ensuring SKILL.md stays lean for efficient context usage by the agent.