skill-creator

Guide authors to create standards-compliant skill packages with SKILL.md frontmatter.

1|Updated Feb 16, 2026
One-click install
npx skills add https://github.com/hayatosc/dotfiles --skill skill-creator-hayatosc
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/hayatosc/dotfiles/tree/main/home/dot_agents/skills/skill-creator
Command: npx skills add https://github.com/hayatosc/dotfiles --skill skill-creator-hayatosc

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill helps authors and engineers create consistent, token-efficient skill packages by enforcing minimal, clear SKILL.md frontmatter, recommending resource organization, and providing tooling to avoid duplicated or excessive context.

Core Features & Use Cases

  • Metadata guidance: Clear requirements for SKILL.md frontmatter (name and description) and advice on what belongs in the body versus references.
  • Tooling for authors: Includes init, validation, and packaging scripts to bootstrap skills, validate frontmatter and structure, and produce distributable .skill files.
  • Organizational patterns: Progressive disclosure guidance for when to include scripts, references, and assets to keep context small and load only what's needed.
  • Use case: Onboard a developer or writer to create a new skill that integrates a deterministic script and long-form references without bloating the agent's context.

Quick Start

Run the initializer to create a skill scaffold, edit SKILL.md to complete name and description, add any scripts/references/assets, then validate and package the skill.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I create standards-compliant SKILL.md frontmatter for AI agent packages?

To create AI agent packages, define the required name and description fields in your SKILL.md frontmatter. This metadata establishes the foundational structure, ensuring your skill meets token-efficient standards and integrates properly with agent workflows.

What is progressive disclosure when building reusable AI skills?

Progressive disclosure is an organizational pattern that keeps AI skill context small by loading only necessary scripts, references, and assets. This approach prevents context bloat by deferring long-form reference loading until the agent specifically requires that information.

How do I validate and package skill packages with helper scripts?

You validate and package skill packages by running the included helper scripts to check SKILL.md frontmatter and structure. Once validated, the packaging script produces distributable .skill files, ensuring your standards-compliant skill is ready for deployment.

Does the skill-creator tooling work with YAML dependencies for metadata validation?

Yes, the skill-creator tooling works with the YAML dependency to parse and validate SKILL.md frontmatter. This ensures your metadata meets standards-compliant requirements for name and description fields during the skill initialization process.

Can I include deterministic scripts and long-form references without bloating agent context?

Yes, you can include deterministic scripts and references without bloating context by following progressive disclosure patterns. Place long-form content in separate reference files and load them only when the agent needs specific domain knowledge for a workflow.

What's the best way to bootstrap a new skill scaffold for technical writers?

The best way to bootstrap a skill scaffold is running the initializer script, which creates the base structure for technical writers. You then edit SKILL.md to add name and description, include any scripts or references, and validate before packaging.