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sarjangi
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prompt-creator

Create, optimize, and test GitHub Copilot prompt files and agent skills.

Updated Mar 6, 2026
Search Tags:#automation#testing#prompt engineering#agent skills#customization#copilot
One-click install
npx skills add https://github.com/sarjangi/Copilot-Customer --skill prompt-creator-sarjangi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-creator
Source: https://github.com/sarjangi/Copilot-Customer/tree/main/tools/skill-creator
Command: npx skills add https://github.com/sarjangi/Copilot-Customer --skill prompt-creator-sarjangi

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines the creation and improvement of GitHub Copilot customizations, making it easier to build reusable AI workflows.

Core Features & Use Cases

  • Customization Creation: Helps generate new prompts, instructions, and agent skills from scratch.
  • Optimization: Assists in refining existing customizations for better performance.
  • Testing & Benchmarking: Facilitates the creation of test cases and evaluation of results.
  • Use Case: You want to create a new Copilot prompt to automatically generate commit messages. This Skill guides you through drafting the prompt, setting up tests, evaluating the output, and iterating until it's perfect.

Quick Start

Use the prompt-creator skill to help me draft a new prompt for generating unit tests.

Frequently Asked Questions about prompt-creator

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

FAQPage Schema
How do I create custom GitHub Copilot instructions and agent skills?▼

Creating custom Copilot instructions involves drafting prompt files, setting up test cases, evaluating the generated outputs, and iterating through refinement cycles to ensure the agent skills perform reliably for your specific automation workflows.

What is the best way to optimize existing Copilot prompt files for better performance?▼

The best way to optimize existing Copilot prompt files is to establish baseline test cases, evaluate current outputs against expected results, and apply iterative refinements to the instructions to improve overall automation accuracy and reliability.

Can I test and benchmark GitHub Copilot customizations before deploying them?▼

Yes, you can test and benchmark GitHub Copilot customizations by generating specific test cases, evaluating the prompt outputs against expected results, and refining the instructions through guided testing methodologies to ensure quality before deployment.

Do I need prior prompt engineering experience to build Copilot customizations?▼

You need a foundational understanding of Copilot customization formats and evaluation methodologies to effectively build and refine customizations, as the process relies on iterative development through guided testing rather than generating prompts without validation.

How does iterative development work for refining AI agent skills?▼

Iterative development for refining agent skills works by drafting the initial prompt, setting up targeted test cases, evaluating the output quality, and repeating the refinement process until the customization meets your specific automation requirements.

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