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hexian2001
hexian2001COMMUNITY
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skill-creator

Draft, test, and benchmark AI skill instructions with automated trigger optimization.

31|5|Updated Jun 19, 2026
Search Tags:#automation#skill development#testing#prompt engineering#benchmarking#ai engineering
One-click install
npx skills add https://github.com/hexian2001/lingxiao-coding --skill skill-creator-hexian2001
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/hexian2001/lingxiao-coding/tree/main/skills/bundled/skill-creator
Command: npx skills add https://github.com/hexian2001/lingxiao-coding --skill skill-creator-hexian2001

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill streamlines the complex process of developing, refining, and validating custom AI skills, ensuring they are robust, accurate, and ready for production use.

Core Features & Use Cases

  • Iterative Development: Provides a structured loop for drafting, testing, and improving skill instructions based on real-world performance.
  • Quantitative Benchmarking: Automates the generation of test cases, execution of runs, and aggregation of metrics to measure skill effectiveness.
  • Trigger Optimization: Uses a dedicated loop to refine skill descriptions, ensuring the AI invokes the skill exactly when needed.
  • Use Case: If you are building a specialized coding assistant, use this skill to create a draft, run it against a suite of coding challenges, evaluate the results, and automatically optimize the skill's description to improve triggering accuracy.

Quick Start

Use the skill-creator to help me draft a new skill for automating my daily project status reports.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I build and test custom AI skills iteratively?▼

To benchmark AI skill performance, you automate the generation of test cases, execute test runs, and aggregate quantitative evaluation metrics to measure the skill's effectiveness and robustness before production use.

How do I optimize AI skill triggering descriptions for accurate model invocation?▼

Optimizing AI skill triggering descriptions involves using a dedicated refinement loop that iteratively adjusts the text to ensure the AI model invokes the skill exactly when needed during execution.

What is the best way to manage AI skill test cases and execution transcripts?▼

The best way to manage AI skill test cases and execution transcripts is by using a structured workspace designed to store runs, aggregate metrics, and track iterative improvements throughout the skill lifecycle.

Do I need a structured workspace to refine prompt engineering for AI skills?▼

Yes, you need a structured workspace to refine prompt engineering for AI skills because it manages the execution transcripts, test cases, and quantitative evaluation metrics required for iterative development.

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