skill-creator

Generate, validate, and package self-contained Skill Units with YAML frontmatter.

1|Updated Jan 16, 2026
One-click install
npx skills add https://github.com/0xdsgnrd/dynamous-hackathon --skill skill-creator-0xdsgnrd
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/0xdsgnrd/dynamous-hackathon/tree/main/meta-skill-creator
Command: npx skills add https://github.com/0xdsgnrd/dynamous-hackathon --skill skill-creator-0xdsgnrd

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires PyYAML, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The Skill Creator enables teams to rapidly generate self-contained Skill Units for AI agents, with consistent structure, frontmatter, and ready-to-use resources.

Core Features & Use Cases

  • Scaffold: generate a complete Skill Unit with an accurate SKILL.md frontmatter and example bundled resources.
  • Validation: perform structural checks to ensure frontmatter correctness and packaging readiness.
  • Packaging: create distributable .skill archives for sharing and deployment across projects.
  • Templates: provide reusable patterns for scripts, references, and assets to jump-start new skills.

Quick Start

Use the Skill Creator to scaffold a new skill and then validate and package it. For example:

  • Run: python3 scripts/init_skill.py my-new-skill --path skills/public
  • Validate: python3 scripts/quick_validate.py skills/public/my-new-skill
  • Package: python3 scripts/package_skill.py skills/public/my-new-skill

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I automate Skill creation for AI agents with consistent YAML frontmatter?▼

To automate Skill creation, you can scaffold a complete Skill Unit with accurate SKILL.md YAML frontmatter and bundled resources, then validate and package it into a distributable .skill archive for deployment.

What's the best way to validate a modular AI agent skill before packaging?▼

The best way to validate a modular AI agent skill is to run a structural check script that enforces YAML frontmatter correctness and packaging readiness, ensuring the self-contained Skill Unit is ready for deployment.

How do I package reusable agent capabilities into a distributable archive?▼

You package reusable agent capabilities into a distributable archive by running a packaging script that bundles the validated Skill Unit directory into a .skill file for sharing across projects.

Do I need PyYAML to scaffold and validate self-contained Skill Units?▼

Yes, you need the PyYAML dependency installed to parse and enforce the YAML frontmatter structure required during Skill Unit scaffolding, validation, and packaging.

Can I use templates to generate scripts, references, and assets for new AI agent skills?▼

Yes, you can use provided reusable templates for scripts, references, and assets to jump-start new AI agent skills, ensuring modular capabilities maintain a consistent structure across domains.

Why does my AI agent skill validation fail during structural checks?▼

AI agent skill validation fails during structural checks when the SKILL.md file lacks the required YAML frontmatter fields, specifically the mandatory name and description properties needed for packaging readiness.