Skill UI

Streamlines the process of providing code review feedback by enforcing a highly structured, ultra-compressed format. It guides users to cut through noise and deliver actionable, single-line comments (Location: Problem. Fix.) while maintaining critical context like severity and technical rationale. Ideal for team settings prioritizing efficiency and high code quality.

This utility compresses natural language memory files (like notes, todos, or preferences) into a concise 'caveman' format. It achieves significant token reduction for large text inputs by systematically removing filler words, articles, and redundant phrasing, while rigorously preserving all technical content, code blocks, URLs, and structural integrity. Ideal for optimizing knowledge bases and saving API/LLM input costs.

This comprehensive guide provides detailed procedural steps for configuring and executing CodeQL code scanning. It covers both implementing automated workflows using GitHub Actions (`codeql.yml`) and running scans via the CodeQL CLI. Users will learn how to manage language matrices, set build modes, interpret SARIF outputs, handle monorepo structures, and troubleshoot complex security analysis setups across multiple languages (e.g., Python, Java, C++).

Copilot Spaces allow users to consolidate and manage project-specific knowledge, including documentation, code snippets, architectural standards, and operational instructions. By loading a Space, Copilot grounds its responses not just on general knowledge, but on the curated, authoritative context of the entire project, enabling accurate Q&A, code generation, and workflow execution based on team standards. Ideal for onboarding, large-scale projects, and maintaining consistency.

This guide provides a detailed template and directive for generating machine-readable, deterministic implementation plans. It is designed for complex software development tasks, such as adding new features, refactoring existing code, or designing system architecture. The output ensures that all steps are atomic, measurable, and structured for autonomous execution by AI agents or human teams, minimizing ambiguity and dependency.

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.

A comprehensive guide for resolving complex timezone issues in .NET and C# applications. It provides production-safe patterns for handling location lookups, converting between Windows and IANA timezone IDs, managing Daylight Saving Time (DST), and ensuring cross-platform compatibility. Includes ready-to-use code snippets for TimeZoneInfo, NodaTime, and DateTimeOffset.

This guide outlines comprehensive best practices for documenting Java code using Javadoc comments. It covers how to properly document public, protected, package-private, and private members, along with the correct usage of various tags like @param, @return, @throws, @see, and specialized syntax for code snippets and versioning. Following these standards ensures API documentation is accurate, maintainable, and adheres to professional Java development norms.

This comprehensive guide outlines best practices for writing robust JavaScript and TypeScript unit tests using the Jest framework. It covers essential topics including proper test structure, effective dependency mocking strategies (using jest.mock and jest.spyOn), handling asynchronous code, implementing snapshot testing, and modern techniques for testing React components with React Testing Library. It also provides a detailed reference of common Jest matchers.

A powerful tool that converts complex Unified Modeling Language (UML) diagrams—such as Sequence, Class, Activity, and State diagrams—into plain text ASCII art. This is crucial for documentation in environments that do not support image embedding, such as terminal sessions, README files, or Git commit messages. Supports both standard ASCII and enhanced Unicode ASCII formats for better visual fidelity.

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 guide and checklist for identifying potential risks when migrating database applications from Oracle to PostgreSQL. It systematically cross-references code and migration artifacts against known behavioral differences, covering issues such as empty string handling, refcursors, type coercion, sorting logic, and timestamp semantics. Use this tool during the planning phase to proactively mitigate risks, or during validation to ensure comprehensive integration test coverage for the new PostgreSQL environment.