Skill UI

A comprehensive toolkit for the full software development lifecycle. It guides stack selection using a detailed decision engine, automatically scaffolds complex boilerplate projects across multiple popular stacks (Next.js, MERN, FastAPI, Django), and provides deep code quality analysis. Features include security vulnerability detection, complexity scoring, and dependency auditing, ensuring high-quality development from the start.

A comprehensive guide to configuring and utilizing ShellCheck for static analysis of shell scripts (Bash, sh, POSIX). This tool detects common programming pitfalls, enforces best practices, and helps ensure script reliability and portability. Ideal for setting up linting in CI/CD pipelines, pre-commit hooks, or maintaining code quality standards across a development team.

A comprehensive tool designed to audit the quality, relevance, and redundancy of all Claude skills and commands. It supports two modes: a rapid incremental scan for recently changed skills, and a deep full stocktake using AI judgment and expert checklists to assess viability (Keep, Improve, Update, Retire, Merge).

This skill provides comprehensive guidelines for architecting and developing high-quality, maintainable software. It is deeply rooted in Clean Architecture and Domain-Driven Design (DDD) principles. It covers best practices for code decomposition, naming conventions, separation of concerns, and avoiding common anti-patterns. Use this skill when designing, analyzing, or developing complex, domain-specific software systems.

Automate the entire Supabase development lifecycle within CI/CD pipelines using GitHub Actions. This tool links projects, validates database migrations, deploys Edge Functions, generates TypeScript types, and runs comprehensive tests against local Supabase instances. Essential for maintaining robust code quality and ensuring schema consistency before deployment.

This expert skill acts as a master orchestrator for Test-Driven Development (TDD), guiding users through the complete Red-Green-Refactor cycle. It specializes in coordinating complex, multi-agent testing workflows, integrating modern practices like BDD, ATDD, and AI-assisted test generation. Use it to ensure robust, highly maintainable, and thoroughly tested software systems across diverse technological stacks and complex development pipelines.

A detailed, multi-phase workflow that strictly enforces the Test-Driven Development (TDD) discipline using the Red-Green-Refactor cycle. This guide covers the entire software development lifecycle, from test specification and architecture design to minimal implementation, rigorous refactoring, and comprehensive integration testing. It mandates high code and test coverage (e.g., 80% line coverage) to ensure robust, maintainable, and high-quality production code.

This skill provides expertise in building robust, scalable, and intelligent test automation ecosystems. It covers AI-powered test generation, self-healing tests, Test-Driven Development (TDD), cross-platform automation (Web/Mobile/API), advanced CI/CD integration, and comprehensive quality engineering practices, ensuring high quality across the entire software development lifecycle.

A specialized skill designed to ensure robust software quality by covering the entire testing lifecycle. This includes defining test strategies, writing unit, integration, and E2E tests, and implementing advanced testing types like performance (k6), security (OWASP), and functional testing. It guides users through coverage analysis, debugging flaky tests, and generating detailed defect and quality reports.

This skill acts as an expert test automation specialist, capable of analyzing source code across multiple languages (Python, JavaScript, TypeScript, etc.). It generates comprehensive, maintainable unit test suites using best practices, maximizing code coverage, and specifically targeting edge cases and exception handling. Use it to ensure high code quality and structural consistency.

This expert skill validates the deployment readiness of Vertex AI Agent Engines. It executes a weighted audit across five critical dimensions: security, monitoring, performance, compliance, and best practices. The output provides a comprehensive 0-100% composite score, a detailed pass/fail report for each check, and a prioritized, actionable remediation plan, ensuring high-quality, production-grade deployments.

Configures robust CI/CD pipelines for Vercel projects using GitHub Actions. This guide automates the full deployment lifecycle, including generating preview environments on every pull request, performing reliable production builds upon merging to main, and implementing test gating to ensure code quality before release. Ideal for professional web development workflows.