code▌

This skill helps you systematically refactor legacy code to improve maintainability, readability, and performance while preserving existing functionality. It follows industry best practices for safe refactoring with comprehensive testing.

Automated frontend code review against a multi-category checklist, supporting both pending-change and targeted file reviews. \n \n Triggers on user requests to review frontend files ( .tsx , .ts , .js ) and applies a canonical checklist across Code Quality, Performance, and Business Logic categories \n Supports two review modes: pending-change review for staged/working-tree files before commit, and file-targeted review for specific named files \n Flags violations with urgency metadata (Urgent vs

Behavioral guidelines to reduce common LLM coding mistakes, focusing on simplicity and clarity in coding practices.

Expert code explanation through narratives, diagrams, and step-by-step breakdowns for all skill levels. \n \n Transforms complex algorithms, system architectures, and design patterns into clear, progressive explanations with visual aids \n Ideal for onboarding walkthroughs, learning materials, and debugging reasoning across codebases \n Delivers high-level flow summaries followed by detailed component breakdowns, pseudocode, and annotated snippets \n Highlights pitfalls, edge cases, and key term

Use this skill whenever the user asks to review, analyze, or improve backend code (e.g., .py) under the api/ directory. Supports the following review modes:

Grounds every implementation decision in official documentation for authoritative, source-cited code.

CLI tools for Svelte 5 documentation lookup and code analysis with built-in autofixer. \n \n Three core commands: list-sections to browse available docs, get-documentation to fetch full documentation for specific topics, and svelte-autofixer to analyze code and suggest fixes \n Autofixer supports Svelte 4 and 5 targeting via --svelte-version flag and async mode via --async option \n Accepts both inline code (with escaped $ characters) and file paths for analysis \n Designed for use within the sv

Comprehensive SQL security, performance, and quality analysis across MySQL, PostgreSQL, SQL Server, and Oracle databases. \n \n Analyzes SQL injection vulnerabilities, access control issues, and sensitive data exposure with parameterized query examples for each database platform \n Reviews query performance through index strategy, join optimization, and anti-pattern detection (N+1 queries, function misuse in WHERE clauses, overuse of DISTINCT) \n Evaluates code quality including naming conventio

$23

Framework for computational fluid dynamics simulations using Python, supporting various solvers and high-performance computing.