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skill-creator

Create, modify, and evaluate AI skills with Python and benchmarking tools.

Updated May 31, 2026
Search Tags:#skill development#benchmarking#evaluation#AI engineering#skill optimization
One-click install
npx skills add https://github.com/danielorzeata83-a11y/Abc --skill skill-creator-danielorzeata83-a11y
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/danielorzeata83-a11y/Abc/tree/main/.agents/skills/skill-creator
Command: npx skills add https://github.com/danielorzeata83-a11y/Abc --skill skill-creator-danielorzeata83-a11y

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires subagents, scripts, evaluation frameworks, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill Unit addresses the challenges of creating, modifying, and evaluating AI skills, providing a toolkit to streamline the process and enhance performance.

Core Features & Use Cases

  • Skill Creation: Facilitate the creation of new skills from scratch, including capturing user intent, writing SKILL.md files, and organizing skill resources.
  • Skill Modification: Allow for iterative improvement of existing skills through evaluation, feedback, and iterative refinement.
  • Skill Evaluation: Provide tools for evaluating skill performance through testing, benchmarking, and statistical analysis.
  • Use Case: Ideal for AI developers and product managers looking to build, iterate, and optimize AI skills for various applications.

Quick Start

Use the skill-creator skill to start the process of creating a new skill. Provide the desired functionality and expected output, and the skill will guide you through the steps to define the skill's structure and behavior.

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 evaluate AI skills from scratch?▼

You can perform skill modification by running iterative evaluations, analyzing statistical feedback from benchmarking tools, and refining the skill's structure and behavior to achieve optimization.

What's the best way to structure skill development for benchmarking?▼

The best way to structure skill development for benchmarking is to use subagents and scripts that facilitate user intent capture, skill drafting, and statistical analysis for iterative improvement.

Do I need Python to use evaluation frameworks for skill optimization?▼

Yes, you need Python, subagent capabilities, and access to evaluation frameworks to utilize the toolkit for skill creation, testing, benchmarking, and iterative refinement.

Can I use subagents to streamline skill creation and testing?▼

Yes, you can use subagents alongside scripts to streamline skill creation and testing, allowing you to capture user intent and evaluate skill performance through comprehensive benchmarking.

Why does my AI skill performance degrade during iterative improvement?▼

AI skill performance may degrade during iterative improvement if evaluation frameworks are not properly analyzing statistical feedback, requiring you to adjust skill resources and testing protocols.

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