skill-creator

Guide users through defining, testing, and optimizing AI skill specifications.

3|1|Updated Apr 17, 2026

Search Tags:#skill development #AI optimization #performance testing #skill refinement #user feedback

Ready to run

npx skills add https://github.com/diegoknsk/workflow-work-ia --skill skill-creator-diegoknsk

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/diegoknsk/workflow-work-ia/tree/main/skills/skill-creator
Command: npx skills add https://github.com/diegoknsk/workflow-work-ia --skill skill-creator-diegoknsk

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenges of creating, modifying, and optimizing skills for AI systems, ensuring high-quality and performant outcomes.

Core Features & Use Cases

Skill Creation: Assist in designing new skills from scratch.
Skill Improvement: Iterate on existing skills with user feedback.
Performance Evaluation: Measure skill performance through testing and analysis.
Use Case: When a user needs to develop a new skill for data analysis or decision-making and requires a systematic approach to skill refinement.

Quick Start

Create a new skill for data visualization by describing the intended functionality and expected input/output formats.

Frequently Asked Questions about skill-creator

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

FAQPage Schema

How do I develop and refine an AI skill for data analysis?▼

Skill creation involves systematically defining specifications, testing, and optimization to ensure high-quality performance for data analysis. It guides you through collecting requirements and iterating with feedback to achieve the desired outcome.

What is the best way to test AI skill performance and quality?▼

Testing AI skill performance requires systematic evaluation and analysis to measure quality against expected outcomes. You apply performance testing techniques to identify areas for skill refinement based on user feedback and specific criteria.

Can I use this approach to create a new skill from scratch?▼

Yes, skill creation from scratch is supported by describing the intended functionality and expected input/output formats. The systematic approach guides you through defining specifications and testing to build the skill.

How do I optimize an existing AI skill using user feedback?▼

Optimizing an existing AI skill uses user feedback to iterate on specifications and logic, improving performance. You refine the skill by analyzing the feedback and making targeted adjustments to achieve better outcomes.

When do I need a systematic approach to AI skill refinement?▼

A systematic approach to skill refinement is needed when skill quality and performance are critical, such as for decision support or content generation. It ensures the skill meets high-quality and performant outcome standards.