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xurenlu
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skill-creator

Creates and iteratively improves AI skills with SKILL.md and test cases.

1|Updated Feb 24, 2026
Search Tags:#skill development#testing#prompt engineering#optimization#AI agent#evaluation
One-click install
npx skills add https://github.com/xurenlu/marstaff --skill skill-creator-xurenlu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/xurenlu/marstaff/tree/main/skills/skill-creator
Command: npx skills add https://github.com/xurenlu/marstaff --skill skill-creator-xurenlu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the entire process of creating and improving AI skills, from initial concept to performance optimization.

Core Features & Use Cases

  • Skill Creation: Guides users through defining intent, writing SKILL.md, and setting up initial tests.
  • Iterative Improvement: Facilitates testing, evaluation, and refinement based on user feedback and performance metrics.
  • Description Optimization: Enhances skill triggering accuracy through automated prompt testing and analysis.
  • Use Case: You have an idea for a new AI assistant capability. Use this Skill to draft the SKILL.md, create test cases, run evaluations, and iterate on the skill's logic and description until it performs optimally.

Quick Start

Use the skill-creator to help me build a new skill for summarizing code files.

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 test AI skills from scratch?▼

Creating AI skills involves defining intent, drafting a SKILL.md file, generating test cases, and running evaluations. This iterative process refines skill logic and descriptions using baseline comparisons and performance metrics.

What is the best way to optimize AI agent descriptions for accurate triggering?▼

Optimizing AI agent descriptions requires automated prompt testing and performance analysis. By evaluating triggering accuracy through quantitative and qualitative feedback loops, you can iteratively refine the skill description for optimal results.

How does baseline comparison work in AI skill evaluation?▼

Baseline comparison in AI skill evaluation measures current performance against previous versions. By running test cases and analyzing performance metrics, you identify areas for iterative improvement in your prompt engineering and skill logic.

Can I use this workflow to improve an existing prompt engineering project?▼

Yes, you can improve an existing prompt engineering project by running evaluations with baseline comparisons. The evaluation framework provides quantitative and qualitative feedback loops to help you refine the skill's logic and description.

Do I need external evaluation frameworks to test AI skills?▼

The skill creation process integrates with evaluation frameworks to provide quantitative and qualitative feedback. This integration allows you to run test cases, analyze performance metrics, and refine descriptions without manually building testing infrastructure.

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