How do I validate a skill I've created?

The skill-creator includes a Python validation script (validate_skill.py) that checks for mandatory frontmatter, file structure, and adherence to quality standards.

What is 'Progressive Disclosure' in skill design?

It is a strategy where only essential information is kept in the main SKILL.md, while detailed documentation is moved to the references/ folder to be loaded only when needed.

When should I use a script instead of a text instruction?

Use scripts for 'low freedom' tasks that are fragile or requires strict consistency, such as file conversions or complex deployments, where deterministic output is required.

What is the purpose of the skill-creator?

It provides a standardized framework and guide for building high-quality Claude Code skills that are efficient, modular, and easy to maintain.

Claude Skill Creator

Name: Claude Skill Creator
Author: CAPHTECH

byCAPHTECH

0•

Herramientas para Desarrolladores

Guides the design, implementation, and validation of custom Claude Code skills using established best practices for context efficiency.

The Claude Skill Creator is a specialized meta-tool designed to help developers build, update, and optimize custom capabilities for Claude Code. It streamlines the skill development lifecycle by enforcing core principles like conciseness and progressive disclosure, ensuring that skills are both performant and easy for Claude to interpret. By providing a standardized structure for SKILL.md, reference documents, and executable scripts, this tool enables users to create robust AI-driven workflows that maximize context window utility and minimize token waste.

Características Principales

01Context window optimization using progressive disclosure principles

020 GitHub stars

03Standardized skill structure generation (SKILL.md, references, scripts, assets)

04Guidance on choosing between text instructions, pseudo-code, and scripts

05Multi-model testing strategies for Haiku, Sonnet, and Opus

06Automated initialization and validation via shell and Python scripts

Casos de Uso

01Optimizing existing skills to reduce token consumption and improve execution reliability

02Refactoring large, monolithic prompts into modular and maintainable Claude skills

03Bootstrapping a new domain-specific skill for specialized development workflows

Características Principales

01Context window optimization using progressive disclosure principles

020 GitHub stars

03Standardized skill structure generation (SKILL.md, references, scripts, assets)

04Guidance on choosing between text instructions, pseudo-code, and scripts

05Multi-model testing strategies for Haiku, Sonnet, and Opus

06Automated initialization and validation via shell and Python scripts

Casos de Uso

01Optimizing existing skills to reduce token consumption and improve execution reliability

02Refactoring large, monolithic prompts into modular and maintainable Claude skills

03Bootstrapping a new domain-specific skill for specialized development workflows