skill-creator

Create and evaluate Claude Code skills with SKILL.md files.

Updated Mar 24, 2026
One-click install
npx skills add https://github.com/bwgz/teambuilder --skill skill-creator-bwgz
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/bwgz/teambuilder/tree/main/teambuilder-sdd/.claude/skills/skill-creator
Command: npx skills add https://github.com/bwgz/teambuilder --skill skill-creator-bwgz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyyaml.

What problem does it solve?

Automates the end-to-end process of creating new skills, editing existing ones, and evaluating their performance, enabling teams to iterate quickly from draft to deployed skill with measurable triggering accuracy.

Core Features & Use Cases

  • Capture Intent: Define what the skill should enable and when it should trigger.
  • Interview and Research: Ask edge-case questions and outline success criteria and dependencies.
  • Write the SKILL.md: Produce a structured entry with name, description, and practical guidance.
  • Run evals and iterate: Create test prompts, run eval loops, analyze results, and rewrite the skill.
  • Description optimization: Optionally refine the triggering description based on eval results to improve triggering accuracy.

Quick Start

Draft a new skill by outlining its purpose, create a SKILL.md with a clear name and description, and begin an eval loop to iteratively improve it.

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 refine Claude Code skills iteratively?

You can create and refine Claude Code skills by capturing intent, writing a structured SKILL.md, running eval loops, and optimizing the description to improve triggering accuracy. This structured workflow ensures measurable quality from draft to deployment.

What is the best way to evaluate prompt engineering accuracy for custom skills?

Evaluating prompt engineering accuracy involves creating test prompts, running eval loops, and analyzing the results to iteratively rewrite the skill. Description optimization based on these eval results maximizes the triggering accuracy of the skill.

How does an iterative eval workflow improve skill creation?

An iterative eval workflow improves skill creation by running test prompts, analyzing failures, and rewriting the SKILL.md. This loop refines the skill's intent capture and optimizes its triggering description for accurate activation.

Do I need pyyaml to use the skill-creation workflow?

Yes, pyyaml is a required dependency for this skill-creation workflow. You need the pyyaml package installed in your environment to parse configurations and generate the structured SKILL.md files during the intent capture phase.

Can I edit existing Claude skills instead of starting from scratch?

Yes, you can edit existing Claude skills by resuming the structured workflow. The process supports modifying existing SKILL.md files, running new eval loops, and optimizing the description to improve triggering accuracy for updated requirements.