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skill-creator

Create, optimize, and measure skills in a Python environment.

1|Updated Apr 11, 2026
Search Tags:#skill development#skill creation#machine learning#skill optimization#performance measurement
One-click install
npx skills add https://github.com/ARALREZ/dyskretny-ai --skill skill-creator-aralrez
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/ARALREZ/dyskretny-ai/tree/main/losssim-pro/.agents/skills/skill-creator
Command: npx skills add https://github.com/ARALREZ/dyskretny-ai --skill skill-creator-aralrez

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps users efficiently create, modify, and optimize skills, as well as measure their performance, saving time and improving accuracy.

Core Features & Use Cases

  • Skill Creation: Design and build new skills from scratch, with support for various functionalities.
  • Skill Optimization: Refine existing skills based on performance metrics and user feedback.
  • Performance Measurement: Benchmark skill performance and make data-driven decisions to enhance accuracy.

Quick Start

Create a new skill for processing invoices and generating reports using the 'skill-creator' skill.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I optimize an existing skill based on performance metrics?▼

To optimize a skill, you refine its description and logic using performance measurement data. This toolset supports iterative skill development by benchmarking accuracy and applying data-driven adjustments to enhance functionality.

What is the best way to measure machine learning skill performance?▼

Measuring machine learning skill performance requires benchmarking accuracy against defined metrics. This toolset provides evaluation tools to benchmark performance and make data-driven decisions to enhance overall accuracy.

Do I need a Python environment to create and evaluate skills?▼

Yes, skill creation and performance evaluation require a Python environment. The process specifically relies on subagents to enable parallel execution and comprehensive analysis during optimization.

Can I use subagents for parallel execution during skill development?▼

Yes, subagents are required to support parallel execution and analysis. This allows you to efficiently handle comprehensive skill creation and optimization tasks within the Python environment.

How do I create a new skill for processing invoices and generating reports?▼

You can create a new skill for processing invoices and generating reports by using the skill creation features. This toolset allows you to design and build new skills from scratch with support for various functionalities.

What are the limitations of iterative skill optimization?▼

Iterative skill optimization is limited by the dependency on a Python environment and subagent availability. Without these prerequisites, the parallel execution and performance measurement required for refinement cannot function.

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