Skill Linter

What it does

The Skill Linter analyzes text files representing AI agent skills to ensure they adhere to specific formatting and content guidelines. It checks for compliance with required frontmatter, structural rules (like directory naming and file existence), and content quality standards—such as avoiding ASCII art, decorative quotes, or unnecessary persona statements. The goal is to improve the clarity, efficiency, and discoverability of skills within a marketplace environment.

When to use it

This skill is useful in these scenarios:

• Adding new skills to a marketplace.
• Reviewing pull requests (PRs) for existing skills.
• Running quality checks before merging changes into a codebase.
• Ensuring that existing skills meet established compliance standards.

Key capabilities

• Frontmatter Validation: Checks required and optional frontmatter fields against defined constraints (e.g., name length, description content).
• Structural Rule Enforcement: Verifies directory names match skill names, mandatory files exist, and disallowed files are absent.
• Content Quality Analysis: Identifies and flags issues like ASCII art, decorative quotes, persona statements, and unnecessary lines.
• Description Routing Quality Assessment: Evaluates the clarity and effectiveness of skill descriptions in defining usage scenarios and expected outputs.

Example prompts

Here are some examples of how you might use this skill:

• "Analyze skill-example/SKILL.md for compliance."
• "Check the quality of the description in my-new-skill/SKILL.md."
• "Run a full linting check on all skills in the skills/ directory."

Tips & gotchas

• The skill requires access to the text files being analyzed (typically .md files).
• Skill descriptions should focus on when and how to use the skill, not on adopting a persona.
• Pay attention to warnings related to description routing quality; these indicate areas where the description could be improved for better discoverability and usability.