skill-creator

Create and validate modular AgentSkills packaged as .skill files.

Updated Mar 13, 2026
One-click install
npx skills add https://github.com/Yogi-076/Vajrascan.on --skill skill-creator-yogi-076
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/Yogi-076/Vajrascan.on/tree/main/moltbot/skills/skill-creator
Command: npx skills add https://github.com/Yogi-076/Vajrascan.on --skill skill-creator-yogi-076

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Creating, structuring, and packaging AgentSkills is repetitive and error-prone without clear templates and validation; this Skill provides the procedures, templates, and tooling to standardize skill creation so teams can produce consistent, distributable skill packages quickly.

Core Features & Use Cases

  • Template initialization: Provides an init script that generates a SKILL.md template and optional resource directories for scripts, references, and assets.
  • Validation and packaging: Includes quick validation and packaging utilities to enforce frontmatter rules and produce .skill distributables.
  • Resource guidance: Advises on when to include scripts, references, and assets and how to structure them for progressive disclosure.
  • Use Case: Use when onboarding a new skill, enforcing naming/frontmatter rules, or packaging skills for distribution.

Quick Start

Run the initializer to create a new skill skeleton and then validate and package it using the provided helper scripts.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I create and package reusable AI agent skills?

To create and package reusable AI agent skills, use an initializer script to generate a SKILL.md template with optional directories for scripts, references, and assets, then validate frontmatter rules and output a .skill distributable package.

What is the best way to structure scripts and references for deterministic automation?

Structuring scripts and references for deterministic automation requires organizing them into modular resource directories that support progressive disclosure, ensuring AI agents can access packaged workflows and tool integrations efficiently.

How do I validate skill frontmatter and naming conventions before distribution?

Validating skill frontmatter and naming conventions involves running a quick validation utility that enforces structural rules and metadata standards, ensuring your packaged skill meets distribution requirements before generating the final output.

Can I use Python scripts and pyyaml dependencies when building skill packages?

Building skill packages supports Python scripts and requires the pyyaml dependency, allowing you to define automation workflows, include reference materials, and package assets into validated .skill files for AI agent integration.

Does this skill creation workflow support packaging documentation and reusable assets?

Skill creation workflows support packaging documentation and reusable assets by providing an init script that generates skeleton directories, allowing teams to bundle references, scripts, and assets into consistent, distributable skill packages.

Why does my skill packaging fail frontmatter validation rules?

Skill packaging fails frontmatter validation rules when the SKILL.md metadata does not meet naming conventions or required structural fields, which the included validation utility detects before producing the final .skill distributable.