skills

Index and validate AI Skill units by detecting SKILL.md files with frontmatter.

Updated Apr 15, 2026
One-click install
npx skills add https://github.com/athan-dial/skills --skill skills-athan-dial
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skills
Source: https://github.com/athan-dial/skills/tree/main/plugins/folio
Command: npx skills add https://github.com/athan-dial/skills --skill skills-athan-dial

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill directory enables users to identify, understand, and utilize AI and automation skills efficiently across complex workflows.

Core Features & Use Cases

  • Skill Discovery: Automatically identify valid self-contained Skill units within repositories by detecting SKILL.md files with proper frontmatter.
  • Metadata Extraction: Generate high-quality descriptive metadata, including names, categories, keywords, dependencies, and safety assessments for each Skill.
  • Use Case: For team repositories with multiple plugins or modules, quickly generate an index of available Skills with their capabilities and safety profiles to inform integration decisions.

Quick Start

Use the skills directory to analyze your plugin collections and generate comprehensive Skill metadata for project integration.

Frequently Asked Questions about skills

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

FAQPage Schema
How do I automatically detect and index AI skills in a repository?

Automatically detect and index AI skills by scanning repositories for valid SKILL.md files with proper frontmatter, extracting metadata like names, categories, keywords, and dependencies to generate a comprehensive skill index.

What is skill safety profiling and metadata extraction for AI workflows?

Skill safety profiling and metadata extraction is the process of generating high-quality descriptive metadata, including safety assessments, categories, and dependencies for each validated AI skill unit to inform integration decisions.

How do I validate self-contained AI skill units in multi-component ecosystems?

Validate self-contained AI skill units by checking for mandatory descriptive frontmatter in SKILL.md files, verifying optional resource directories, and performing safety profiling to ensure quality assessment in multi-component ecosystems.

Can I generate a skill index with capabilities and safety profiles for team repositories?

Yes, you can generate an index of available skills with capabilities and safety profiles for team repositories containing multiple plugins or modules, enabling rapid discovery and evaluation for project integration.

Does repository analysis for AI skills require any external dependencies?

No, repository analysis for AI skills operates without external dependencies, automatically detecting SKILL.md files and validating their frontmatter to support skill discovery and safety evaluation natively.

When do I need to run skill discovery and quality assessment on my plugins?

Run skill discovery and quality assessment when managing team repositories with multiple plugins or modules, requiring rapid indexing of available skills, metadata extraction, and safety evaluation for integration planning.