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Found 136 Skills
Python refactoring for readability, maintainability, and performance.
Applies software engineering best practices, design principles, and avoids common anti-patterns. Use when designing systems, reviewing code quality, refactoring legacy code, making architectural decisions, or improving maintainability.
Language-agnostic coding principles for maintainability, readability, and quality. Use when implementing features, refactoring code, or reviewing code quality.
Simplify and refine code for clarity, consistency, and maintainability. Use after writing or modifying code to clean it up while preserving all functionality.
Design software architectures with appropriate patterns for scale, maintainability, and team structure. Covers layered, hexagonal, event-driven, CQRS, and modular monolith architectures. Produces architecture decision records, component diagrams, and dependency maps. Prevents over-engineering, premature distribution, and architectural drift.
Use when optimizing GitLab CI/CD pipelines for performance, reliability, or maintainability. Covers pipeline optimization and organizational patterns.
This skill should be used when analyzing technical debt in a codebase, documenting code quality issues, creating technical debt registers, or assessing code maintainability. Use this for identifying code smells, architectural issues, dependency problems, missing documentation, security vulnerabilities, and creating comprehensive technical debt documentation.
This skill guides writing of new Ruby code following modern Ruby 3.x syntax, Sandi Metz's 4 Rules for Developers, and idiomatic Ruby best practices. Use when creating new Ruby files, writing Ruby methods, or refactoring Ruby code to ensure adherence to clarity, simplicity, and maintainability standards.
Designs and builds reusable Terraform modules. Use when creating reusable infrastructure patterns, encapsulating complex resource groups, standardizing configurations across projects, or organizing code for maintainability. Covers module structure, versioning, composition, and best practices for production modules.
Apply the "How I Made Your Machine" coding style guide to implementation, refactoring, and code review tasks across TypeScript, Rust, and Python. Use when a request asks for this style guide, when improving maintainability and type safety, when modeling domain concepts with explicit variants/types, or when enforcing behavior-first testing.
Replace hardcoded values with constants, enums, and configuration for maintainability; use PHP 8.1+ enums and config files
Test coverage-focused code review. Apply when reviewing code for missing unit tests, integration tests, edge cases, error handling paths, test quality, and test maintainability.