Get best practices for TUnit unit testing, including data-driven tests

Refactoring using Extract Methods in Java Language

Expert skill for building web-based game engines and games using HTML5, Canvas, WebGL, and JavaScript. Use when asked to create games, build game engines, implement game physics, handle collision detection, set up game loops, manage sprites, add game controls, or work with 2D/3D rendering. Covers techniques for platformers, breakout-style games, maze games, tilemaps, audio, multiplayer via WebRTC, and publishing games.

Creates integration test cases for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Generates DB-agnostic xUnit tests with deterministic seed data that validate behavior consistency across both database systems. Use when creating integration tests for a migrated project, generating test coverage for data access layers, or writing Oracle-to-PostgreSQL migration validation tests.

Prompt for creating an Epic Product Requirements Document (PRD) for a new epic. This PRD will be used as input for generating a technical architecture specification.

Expert 10x engineer skill for interpreting and implementing code from shorthand, quasi-code, and natural language descriptions. Use when collaborators provide incomplete code snippets, pseudo-code, or descriptions with potential typos or incorrect terminology. Excels at translating non-technical or semi-technical descriptions into production-quality code.

Create Spring Boot Kotlin Project Skeleton

Generate complete solutions for specific Dataverse SDK use cases with architecture recommendations

Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)

A micro-prompt that reminds the agent that it is an interactive programmer. Works great in Clojure when Copilot has access to the REPL (probably via Backseat Driver). Will work with any system that has a live REPL that the agent can use. Adapt the prompt with any specific reminders in your workflow and/or workspace.

Update an existing specification file for the solution, optimized for Generative AI consumption based on new requirements or updates to any existing code.

Add GET, POST, PATCH, and DELETE operations to a TypeSpec API plugin with proper routing, parameters, and adaptive cards

Analyze Terraform plan JSON output for AzureRM Provider to distinguish between false-positive diffs (order-only changes in Set-type attributes) and actual resource changes. Use when reviewing terraform plan output for Azure resources like Application Gateway, Load Balancer, Firewall, Front Door, NSG, and other resources with Set-type attributes that cause spurious diffs due to internal ordering changes.

Suggest relevant GitHub Copilot instruction files from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing instructions in this repository, and identifying outdated instructions that need updates.

Process media files (video, audio, images, documents) using Transloadit. Use when asked to encode video to HLS/MP4, generate thumbnails, resize or watermark images, extract audio, concatenate clips, add subtitles, OCR documents, or run any media processing pipeline. Covers 86+ processing robots for file transformation at scale.

Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.

Create GitHub Pull Request for feature request from specification file using pull_request_template.md template.

Create a new specification file for the solution, optimized for Generative AI consumption.

Analyze chatmode or prompt files and recommend optimal AI models based on task complexity, required capabilities, and cost-efficiency

Finalize prompt file using the role of an AI agent to polish the prompt for the end user.