Skill UI

This library provides powerful monadic types, including Option, Result, and Either, for Go. It enhances type safety by replacing manual nil checks with type constraints and transforming verbose error handling into composable pipelines. It is essential for adopting modern functional programming patterns and building robust, resilient Go applications.

A comprehensive guide to the Go programming language ecosystem. This resource curates official documentation, essential newsletters, key developer profiles, and community hubs. Use this guide when you need to stay current with Go language features, discover new libraries, or keep up with industry best practices and community discussions.

This guide provides a comprehensive, step-by-step process to scaffold a modern Spring Boot application using Kotlin. It covers downloading the template, configuring dependencies (including SpringDoc and ArchUnit), and setting up complex polyglot environments using Docker Compose. Supports PostgreSQL, MongoDB, Redis, and WebFlux reactive programming.

This guide provides comprehensive best practices for writing robust and high-performance asynchronous code in C#. It covers naming conventions, optimal return types (Task, ValueTask), advanced patterns like the async command pattern, proper exception handling, and crucial performance considerations (e.g., using Task.WhenAll() and avoiding deadlocks with ConfigureAwait(false)). Ideal for developers looking to master modern C# concurrency.

This comprehensive guide outlines best practices for developing high-quality, idiomatic, and maintainable enterprise applications using Kotlin and Spring Boot. It covers architectural patterns, dependency injection using primary constructors, managing state with data classes, implementing robust RESTful APIs, handling transactions, and leveraging Kotlin features like null safety and Coroutines for asynchronous programming. It also provides guidance on modern testing strategies (Kotest, Testcontainers).

An advanced, AI-powered agent designed to generate comprehensive and workable unit tests for virtually any programming language (e.g., Python, C#, Java, Go, TypeScript). It operates via a sophisticated multi-agent pipeline (Research → Plan → Implement → Build → Test → Fix → Lint). This ensures generated tests are not only written following project conventions but also compile, pass all tests, and effectively improve code coverage.

A comprehensive, multi-phase quality engineering audit tool designed to test codebases beyond standard unit tests. It first explores the codebase's domain and architecture to derive behavioral requirements, then executes a rigorous sequence including spec-traced functional tests, three-pass code reviews, and a multi-model specification audit (Council of Three). It is specifically engineered to find the critical 35% of real-world defects that structural code review alone might miss. Works with any programming language.

This micro-prompt guides AI agents to adopt the mindset of an interactive programmer. It emphasizes using the REPL (Read-Eval-Print Loop) for systematic system exploration and modification, treating the system state as the ultimate source of truth. It also reminds the agent to utilize structural editing tools and maintain todo lists, significantly improving the accuracy and efficiency of the development workflow in live coding environments.

Cirq is an open-source Python framework from Google Quantum AI for designing, simulating, and executing quantum circuits. It supports multiple hardware backends (IonQ, Pasqal, etc.) and includes comprehensive tools for noise modeling, circuit optimization, and parameterized experimentation, making it ideal for NISQ device development and advanced quantum computing research.

PyMC is a powerful Python library designed for probabilistic programming and sophisticated Bayesian modeling. It enables users to build complex models, such as hierarchical structures and time series, and perform rigorous inference using methods like MCMC (NUTS) sampling and Variational Inference. Key features include model comparison (LOO, WAIC) and comprehensive diagnostic tools for uncertainty quantification.

This guide identifies and corrects the most common programming mistakes and anti-patterns when integrating with Adobe APIs. It covers critical topics such as migrating from deprecated JWT to OAuth, implementing token caching, handling asynchronous job polling, and secure file uploads. Essential reading for building robust, production-ready Adobe integrations.

This is a detailed offensive checklist for identifying and exploiting insecure deserialization vulnerabilities across multiple programming languages (Java, Python, PHP, .NET, Node.js, etc.). It covers techniques like gadget chain generation, magic method abuse, type confusion, and modern attack vectors, providing a deep methodology for penetration testing and vulnerability research.