sample-ai-skill

Validate AI skills against AI Linter frontmatter and metadata rules.

1|1|Updated Jan 26, 2026

Search Tags:#validation #ai #example #skill #validate #linter

Ready to run

npx skills add https://github.com/fchastanet/ai-linter --skill sample-ai-skill

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: sample-ai-skill
Source: https://github.com/fchastanet/ai-linter/tree/main/examples/sample-skill
Command: npx skills add https://github.com/fchastanet/ai-linter --skill sample-ai-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This sample skill demonstrates how AI Linter expects a well-formed SKILL.md with frontmatter and metadata, enabling automated validation.

Core Features & Use Cases

Demonstrates proper frontmatter formatting and metadata structure for AI skills.
Illustrates validation steps performed by the AI Linter, including reference checks and content length validation.
Serves as a test fixture for verifying skill discovery and parsing in development pipelines.

Quick Start

Provide this sample skill to verify that a new skill directory can be detected and validated by the AI Linter.

Frequently Asked Questions about sample-ai-skill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is AI skill validation and how does it check SKILL.md metadata?▼

AI skill validation checks SKILL.md files for required frontmatter fields, metadata structure, content length, and reference integrity. The linter verifies that mandatory fields like name and description are present to ensure automated discovery and parsing in development pipelines.

How do I validate frontmatter presence in a skill directory?▼

To validate frontmatter presence, provide a single skill directory containing a SKILL.md file to the AI Linter. The validation process detects the directory, parses the file, and verifies that required frontmatter fields like name and description are correctly formatted.

Does the AI Linter check content length and references in SKILL.md files?▼

Yes, the AI Linter performs content length checks and reference validation on SKILL.md files. It ensures metadata meets structural requirements and that references within the skill content are valid, enabling reliable automated parsing.

Can I use this sample skill to test skill discovery in development pipelines?▼

Yes, this sample skill serves as a test fixture for verifying skill discovery and parsing in development pipelines. It demonstrates proper formatting and metadata structure, allowing you to confirm that new skill directories are detected and validated correctly.

What are the limitations of validating a single skill directory with the AI Linter?▼

The AI Linter validation applies to scenarios where a single skill directory is present. It focuses on frontmatter requirements, content length checks, and reference validation, and does not demonstrate multi-directory batch processing or complex pipeline integrations.