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Found 1,381 Skills
Deep code simplification, refactoring, and quality refinement. Analyzes structural complexity, anti-patterns, and readability debt, then applies targeted refactoring preserving exact behavior. Language-agnostic: Python, Go, TypeScript/JavaScript, Rust. Use this skill when the goal is simplification and clarity rather than bug-finding. Triggers on: "simplify this code", "clean up my code", "refactor for clarity", "reduce complexity", "make this more readable", "code quality pass", "tech debt cleanup", "run the code refiner", "simplify recent changes", "this code is messy", "too much nesting", "this function is too long", "clean this up before I PR it", "tidy up my code", cyclomatic complexity, cognitive complexity, code smells.
Enforce Vertical Slice Architecture (VSA) when building applications in any language (Go, .NET/C#, Java, Kotlin, TypeScript, Python, etc.) and any type (web API, mobile backend, CLI, event-driven). Organize code by feature/use-case instead of technical layers. Each feature is a self-contained vertical slice with a single entry point that receives the router/framework handle and its dependencies. Use when the user says "vertical slice architecture", "VSA", "organizar por feature", "feature-based architecture", "slice architecture", or when building a new app or feature and the project already follows VSA conventions. Also use when reviewing or refactoring code to align with VSA principles.
Detects .NET intent for any C#, ASP.NET Core, EF Core, Blazor, MAUI, Uno Platform, WPF, WinUI, SignalR, gRPC, xUnit, NuGet, or MSBuild request from prompt keywords and repository signals (.sln, .csproj, global.json, .cs files). First skill to invoke for all .NET work — loads version-specific coding standards and routes to domain skills via [skill:dotnet-advisor] before any planning or implementation. Do not use for clearly non-.NET tasks (Python, JavaScript, Go, Rust, Java).
SLF4J - Simple Logging Facade for Java. Standard logging API that abstracts underlying implementation (Logback, Log4j2). Provides parameterized logging and MDC support. USE WHEN: user mentions "slf4j", "java logging api", "parameterized logging", asks about "how to log in Java", "logger facade", "MDC in java", "logging best practices java" DO NOT USE FOR: Logback configuration - use `logback` instead, Log4j2 configuration - use Log4j2 skill, Node.js logging - use `winston` or `pino` instead, Python logging - use `python-logging` instead
Google Cloud Platform SDK integration. Cloud Functions, Firestore, Cloud Storage, Pub/Sub, BigQuery, and Cloud Run. Node.js and Python client libraries. USE WHEN: user mentions "GCP", "Google Cloud", "Cloud Functions", "Firestore", "Cloud Storage", "Pub/Sub", "BigQuery", "Cloud Run", "Firebase" DO NOT USE FOR: AWS services - use `aws`; Azure services - use `azure`; Firebase Auth - use auth skills
Java logging with SLF4J facade, Logback, and Log4j2 implementations. Covers configuration, log levels, structured logging, async logging, and production best practices for Spring Boot applications. USE WHEN: user mentions "java logging", "spring boot logging", "slf4j setup", asks about "how to log in java", "logback vs log4j2", "java logging best practices" DO NOT USE FOR: Node.js logging - use `nodejs-logging` instead, Python logging - use `python-logging`, Kotlin-specific logging - similar but has nuances
Optimize code performance through iterative improvements (max 2 rounds). Benchmark execution time and memory usage, compare against baseline implementations, and generate detailed optimization reports. Supports C++, Python, Java, Rust, and other languages.
OpenFGA authorization modeling best practices and guidelines. This skill should be used when authoring, reviewing, or refactoring OpenFGA authorization models. Triggers on tasks involving OpenFGA models, relationship definitions, permission structures, .fga files, .fga.yaml test files, or OpenFGA SDK usage in JavaScript, TypeScript, Go, Python, Java, or .NET.
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).
Generate publication-ready scientific figures in Python/matplotlib with a consistent figures4papers house style. Use when creating or refining academic bar/trend/heatmap/scatter/multi-panel figures, enforcing visual consistency, or exporting paper-ready PNG/PDF/SVG outputs.
Generates production-grade Selenium WebDriver automation scripts and tests in Java, Python, JavaScript, C#, Ruby, or PHP. Supports local execution and TestMu AI cloud with 3000+ browser/OS combinations. Use when the user asks to write Selenium tests, automate with WebDriver, run cross-browser tests on Selenium Grid, or mentions "Selenium", "WebDriver", "RemoteWebDriver", "ChromeDriver", "GeckoDriver". Triggers on: "Selenium", "WebDriver", "browser automation", "Selenium Grid", "cross-browser", "TestMu", "LambdaTest".
This skill should be used when the user asks to "integrate GitHub Copilot into an app", "use the Copilot SDK", "build a Copilot-powered agent", "embed Copilot in a service", or needs guidance on the GitHub Copilot SDK for Python, TypeScript, Go, or .NET.