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Prompt Library

GPTClaudeDeepSeek··593 copies·updated 2026-07-14
prompt-library-4.prompt
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layout: default
title: Prompt Library
nav_order: 4
---

# Prompt Library

Reusable, tested prompts organized by category. Each prompt follows the [standard template](https://github.com/Clipperone/copilot-learning-labs/blob/main/templates/prompt-template.md).

| Category | Description |
|----------|-------------|
| [Generation](https://github.com/Clipperone/copilot-learning-labs/tree/main/prompts/generation) | Generate functions, classes, and components from specifications |
| [Refactoring](https://github.com/Clipperone/copilot-learning-labs/tree/main/prompts/refactoring) | Restructure code for clarity, maintainability, and separation |
| [Debugging](https://github.com/Clipperone/copilot-learning-labs/tree/main/prompts/debugging) | Diagnose and fix bugs with structured context |
| [Testing](https://github.com/Clipperone/copilot-learning-labs/tree/main/prompts/testing) | Generate test suites with coverage intent and edge cases |
| [Documentation](https://github.com/Clipperone/copilot-learning-labs/tree/main/prompts/documentation) | Produce audience-aware documentation |
| [Review](https://github.com/Clipperone/copilot-learning-labs/tree/main/prompts/review) | Systematic code review prompts |
| [Security](https://github.com/Clipperone/copilot-learning-labs/tree/main/prompts/security) | OWASP-scoped vulnerability analysis |
| [Migration](https://github.com/Clipperone/copilot-learning-labs/tree/main/prompts/migration) | Framework and API migration prompts |

Build your own prompts during [Module 04 — Prompt Engineering](modules/04-prompt-engineering) and commit them as part of the capstone.

when to use it

Community prompt sourced from the open-source GitHub repo Clipperone/copilot-learning-labs (MIT). A "Prompt Library" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.

tags

productivitycommunitydeveloper

source

Clipperone/copilot-learning-labs · MIT