Skill UI

This guide provides a comprehensive workflow for configuring a local development environment using Clerk authentication. It covers setting up test keys, seeding test users, configuring hot reloading, and mocking authentication for unit tests, ensuring a robust and isolated development experience.

A comprehensive guide to configuring Clerk for multiple environments (development, staging, production). This setup ensures secure key separation, implements environment-aware configuration logic, and provides best practices for integrating robust key validation and CI/CD deployment pipelines.

A comprehensive workflow bundle covering the entire cloud-native development lifecycle. It guides users through critical phases, including cloud infrastructure setup (AWS, Azure, GCP, Terraform IaC), container orchestration with Kubernetes, robust CI/CD pipeline automation, observability implementation, security hardening, cost optimization, and disaster recovery planning. This ensures best practices across all stages of modern application deployment.

A comprehensive workflow designed to orchestrate the entire lifecycle of large-scale features, from initial requirement gathering and architectural design through multi-service implementation, rigorous testing, and modern deployment strategies (e.g., canary, blue-green). Use this skill when coordinating complex, cross-functional feature delivery across frontend, backend, and data teams, ensuring quality and consistency at every phase.

Master the complete lifecycle of building professional, cross-browser browser extensions for Chrome and Firefox. This expertise covers modern extension architecture, implementing Manifest V3 (MV3), developing content scripts, service workers, and popup UIs. Furthermore, it includes strategies for extension monetization and successful publishing on the Chrome Web Store, ensuring the built tool solves real-world user problems.

This expert skill analyzes codebases to identify, quantify, and prioritize all forms of technical debt—including code complexity, architectural flaws, outdated dependencies, and testing gaps. It calculates the measurable impact of this debt on development velocity, bug rates, and overall business risk. The output provides a comprehensive, actionable, and ROI-driven roadmap for systematic remediation.

This skill helps transform code reviews from simple gatekeeping into a powerful knowledge-sharing mechanism. It guides users through systematic analysis of code changes, focusing on correctness, security, performance, and maintainability. Use it when reviewing pull requests, establishing best practices, or mentoring developers to ensure high-quality, robust codebase development.

Automated skill providing code splitting guidance for frontend development, covering React/Vue/CSS, modern performance and accessibility best practices, and producing validated, production-ready configurations.

This expert analyzes and refactors existing codebases to enhance quality, maintainability, and performance. It specializes in applying clean code principles, SOLID design patterns, and modern software engineering best practices. Use it to clean up technical debt, simplify complex modules, or prepare a codebase for new feature development.

A comprehensive expert system for analyzing software codebases to identify, quantify, and prioritize technical debt across various dimensions (code, architecture, testing, infrastructure). It provides detailed metrics, impact assessments (development velocity, quality loss), and actionable, prioritized remediation roadmaps with clear ROI projections.

This skill executes CodeRabbit's core workflow, providing automated, in-depth code reviews directly on pull requests. It analyzes code diffs based on custom rules (e.g., API validation, DB security), generates detailed walkthrough summaries, and posts line-level feedback. Ideal for setting up robust CI/CD quality gates and maintaining high code standards throughout the development lifecycle.

Configure CodeRabbit CLI to integrate AI-powered code reviews directly into your local development loop. This workflow allows developers to run comprehensive, AI-driven reviews against staged or unstaged changes before committing or pushing to a remote repository. It establishes a crucial 'two-layer' review process, providing instant, fast feedback at the local CLI level, complementing the formal PR review process. This tool is essential for maintaining high code quality and consistency during rapid development cycles.