Skill UI

This comprehensive guide covers universal coding standards, best practices, and architectural patterns for modern web development using TypeScript, JavaScript, React, and Node.js. It emphasizes fundamental principles like Readability, DRY, and Immutability, while providing detailed guidelines on component structure, state management, asynchronous programming, and designing robust REST APIs.

A comprehensive set of architectural and coding standards for building high-reliability, observable, and maintainable backend services. It mandates the use of layered architecture, explicit error handling (Sentry), robust validation (Zod), and strict dependency management for Node.js, Express, and TypeScript projects.

Provides comprehensive guidelines for modern web development, covering critical areas like security best practices (e.g., CSP, HTTPS enforcement, input sanitization), browser compatibility (viewport, encoding), and avoiding deprecated APIs. Use this skill when aiming to audit, modernize, or improve the overall quality and robustness of web code.

Behavioral rules for LLMs writing or reviewing code, emphasizing caution, simplicity, surgical edits, and goal-driven execution to avoid common mistakes during implementation tasks, bug fixes, or refactors.

A comprehensive guide derived from C++ Core Guidelines, enforcing modern, safe, and idiomatic practices for C++17, C++20, and C++23. It emphasizes crucial principles like RAII, type safety, immutability, and proper resource ownership using smart pointers. Use this when writing new features, reviewing existing code, or making architectural decisions to ensure code quality and consistency.

Defines strict guidelines for creating and maintaining Excel financial models, covering zero formula errors, industry color coding, number formatting, documented assumptions, and mandatory use of Excel formulas to ensure accuracy and auditability before recalculation.

A set of behavioral guidelines derived from Andrej Karpathy's observations to help users writing, reviewing, or refactoring code with Large Language Models (LLMs). It guides developers to avoid overcomplication, make surgical changes, explicitly surface assumptions, and define verifiable success criteria, promoting clean, simple, and robust code development.

Behavioral guidelines for writing, reviewing, and refactoring code with LLMs, emphasizing minimalism, clear assumptions, surgical edits, and verifiable success criteria to avoid common machine-assisted coding mistakes.

This comprehensive guide outlines best practices for writing high-quality, scalable, and maintainable code in .NET/C#. It covers core architectural principles, including SOLID, dependency injection, and design patterns (e.g., Command Handler). Furthermore, it addresses modern challenges such as structured logging, async/await patterns, secure coding, robust testing standards, and advanced AI integration using Semantic Kernel.

This guide outlines the structure and content guidelines for an AGENTS.md file. This file serves as a comprehensive 'README for agents,' providing detailed, technical context and operational instructions (such as setup, development workflow, testing procedures, and code style) that enable advanced AI coding agents to interact with and understand a codebase effectively. It greatly complements traditional READMEs by focusing purely on machine-readable technical requirements.

This comprehensive guide helps elevate a UI from merely functional to polished, purposeful, and aesthetically coherent with its domain. It dictates pre-coding design choices, such as defining the audience, tone (e.g., minimal, industrial), and purpose. It provides rigorous guidelines on establishing visual hierarchy, typography, color palettes, and interactions, ensuring the final product feels intentional and professional, rather than generic or templated.

A comprehensive reference guide detailing idiomatic and efficient coding practices in Ruby. It covers essential topics such as using Enumerable methods (map, select), modern string handling, robust error management, and proper module/class structuring. By adhering to these guidelines, developers can write cleaner, less verbose, and highly performant code that truly feels 'Ruby-like'.