Skill UI

A comprehensive guide covering best practices for Terraform and OpenTofu. It provides structured advice on module hierarchy, directory organization, naming conventions, and advanced testing strategies (including native testing and policy as code). Use this skill when designing, refactoring, or implementing robust Infrastructure as Code (IaC) pipelines and multi-environment deployments.

A comprehensive guide for safely upgrading and migrating between Apify core packages, including apify-client, apify, and crawlee. This skill is essential for handling major breaking changes, particularly the transition from Apify SDK v2 to v3, which separated crawling functionality into the dedicated 'crawlee' package. It provides detailed steps for version checking, dependency management, and code refactoring.

This guide details how to use sophisticated coding agents (such as Codex, Claude Code, or Pi) through a structured bash workflow. It provides methods for complex development tasks, including building new features, refactoring large codebases, and reviewing pull requests (PRs). Key best practices covered include managing pseudo-terminals (PTY), defining focused working directories (`workdir`), and executing tasks in the background for robust, multi-step automation.

This guide provides production-ready, structured code patterns for integrating with the Hootsuite REST API using TypeScript and Python. It includes type-safe API clients, timezone-aware scheduling helpers, and cross-platform content formatting utilities. Ideal for building robust, scalable social media management systems or refactoring existing SDK usage.

This skill runs a comprehensive, sequenced pipeline (Patterns 1-5) to structurally analyze a monolithic codebase. It inventories components, detects domain duplication, resolves hierarchy issues, measures inter-module coupling, and groups components into candidate, domain-aligned services. It is essential for architects planning service extraction, providing actionable metrics and DDD insights before refactoring or splitting the application.

This skill guides developers through creating a comprehensive refactoring plan and serving as a Request for Comments (RFC). It orchestrates detailed interviews, codebase analysis, and scope definition. It ensures the refactor is broken down into tiny, safe, incremental commits, culminating in a structured GitHub issue that serves as a definitive architectural and technical decision document.

Test-Driven Development (TDD) is a development methodology that emphasizes writing failing tests first, followed by writing minimal code to pass them (Red -> Green), and finally refactoring the code (Refactor). This approach ensures that code is always verified against its intended public behavior, making the system robust, maintainable, and resilient to internal changes. It teaches developers to focus on 'what' the system does, rather than 'how' it does it.

This tool analyzes and refactors code to detect and correct anemic domain models. It enforces rich domain modeling patterns (Entities, Value Objects, Aggregates, Domain Events), improving encapsulation and business logic ownership. Use it when validating, reviewing, or refactoring core domain logic to ensure adherence to Domain-Driven Design (DDD) principles.

This advanced code reviewer analyzes your codebase through the principles of 12 classic software engineering books (e.g., Clean Code, DDIA, Mythical Man-Month). It detects conceptual flaws, design smells, tight coupling, missing abstractions, and architectural risks—issues that standard linters and basic AI tools often miss. Essential for major refactoring and pre-design validation.

Logic Lens is an advanced AI skill that performs deep, formal logic-driven code review. Unlike standard linters, it analyzes code for complex issues like race conditions, security vulnerabilities (SQL injection, XSS), type safety flaws, and algorithmic errors across 9 critical risk categories. It is ideal for pre-merge PR reviews, auditing sensitive code paths, and refactoring complex business logic.

Cavecrew provides a set of specialized subagents (investigator, builder, reviewer) designed for efficient code development delegation. Unlike vanilla agents, Cavecrew compresses output results, drastically reducing the token usage injected back into the main context. This allows users to maintain context over much longer, complex coding sessions, effectively preventing context exhaustion during large-scale refactoring, debugging, or multi-step feature development.

An expert AI specializing in Slang shader programming for high-performance graphics and compute applications. This model excels at writing, reviewing, refactoring, and optimizing production-grade code for various graphics stages (vertex, fragment, compute, ray tracing, tessellation). It ensures cross-platform compatibility across major APIs (D3D12, Vulkan, Metal, OpenGL) and supports advanced concepts like generics, parameter blocks, and automatic differentiation. Use this skill when integrating shaders into C++ engines or requiring deep knowledge of low-level GPU pipelines.