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.