skill-creator

Design and create Claude Skills with progressive disclosure and YAML frontmatter.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/roeibajayo/claude-tools --skill skill-creator-roeibajayo
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/roeibajayo/claude-tools/tree/main/.claude/skills/skill-creator
Command: npx skills add https://github.com/roeibajayo/claude-tools --skill skill-creator-roeibajayo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill empowers you to design and create custom Claude Skills, transforming repetitive tasks or domain-specific knowledge into reusable, automated capabilities. Stop re-explaining yourself and let AI work for you.

Core Features & Use Cases

  • Progressive Disclosure Design: Structure skills to load information efficiently, keeping core instructions lean and details on-demand.
  • Capture Domain Expertise: Codify project-specific knowledge, API integrations, or framework conventions into reusable units.
  • Automate Repeating Context: Turn frequently used patterns, schemas, or rules into self-contained skills.
  • Use Case: If you find yourself repeatedly explaining a database schema or a specific API workflow to Claude, use this Skill to create a dedicated database-schema or api-client skill that Claude can automatically reference.

Quick Start

To create a new skill:

  1. Create a new directory: .claude/skills/my-skill/
  2. Inside, create SKILL.md with YAML frontmatter (name, description) and core instructions.
  3. Test the skill in a conversation to ensure it triggers correctly.
  4. As needed, add optional references/, scripts/, or assets/ for detailed content.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I create a reusable Claude Skill to automate repetitive tasks?

Create a Claude Skill by building a .claude/skills/my-skill/ directory with a SKILL.md file containing YAML frontmatter (name, description) and core instructions. Use progressive disclosure to structure information across three levels: Level 1 metadata, Level 2 instructions, and Level 3 resources, keeping the core under ~5k tokens. Test in a conversation to validate it triggers correctly.

What is progressive disclosure in Skill design and why does it matter?

Progressive disclosure loads information on-demand rather than all at once, keeping core instructions lean while detailed content stays in optional references, scripts, or assets. This approach improves efficiency by reducing context overhead and letting Claude access domain expertise only when needed during conversations.

How do I capture domain expertise or project-specific knowledge into a Skill?

Codify project patterns, API workflows, database schemas, or framework conventions directly into your Skill's SKILL.md instructions and optional bundled content. Structure repeating context—like frequent explanations or configuration rules—as self-contained skills that Claude can reference automatically without re-explaining each time.

Can I add optional content like scripts or references to my Skill?

Yes. Beyond the required SKILL.md, add optional references/, scripts/, or assets/ directories for detailed content. Scripts must behave deterministically and never load code into context; references store supplementary material that progressive disclosure can retrieve when needed.

What are the character and token limits for a Claude Skill?

YAML frontmatter fields (name and description) have defined character limits. The SKILL.md body is constrained to approximately 5,000 tokens to maintain efficiency while capturing essential domain logic and instructions.

How do I validate that my Skill works correctly in conversations?

Test your Skill by using it in real Claude conversations to confirm it triggers correctly and responds as intended. Iterative refinement through actual usage ensures the workflow is testable, effective, and properly structured across its three-level architecture.