code▌

A disciplined approach to writing code that communicates intent, minimizes surprises, and welcomes change. Apply these principles when writing new code, reviewing pull requests, refactoring legacy systems, or advising on code quality improvements.

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:

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

Delivers changes incrementally to manage large features effectively.

Dispatch code review subagents with focused context to catch issues before they compound. \n \n Integrates with subagent-driven development workflows, triggering review after each task or before merging to main \n Provides code-reviewer subagent with precise git SHAs, implementation details, and requirements, keeping reviewer focused on work product rather than session history \n Categorizes feedback into Critical (fix immediately), Important (fix before proceeding), and Minor (note for later) s

Multi-dimensional code review with quality gates. Every change gets reviewed before merge — no exceptions. Review covers five axes: correctness, readability, architecture, security, and performance.

When explaining code, always include: \n \n Start with an analogy : Compare the code to something from everyday life \n Draw a diagram : Use ASCII art to show the flow, structure, or relationships \n Walk through the code : Explain step-by-step what happens \n Highlight a gotcha : What's a common mistake or misconception? \n \n Keep explanations conversational. For complex concepts, use multiple analogies.

Comprehensive code simplification guide for AI agents and LLMs. Contains 47 rules across 8 categories, prioritized by impact from critical (context discovery, behavior preservation) to incremental (language idioms). Each rule includes detailed explanations, real-world examples comparing incorrect vs. correct implementations, and specific impact metrics.

A coding assistant that promotes minimalism and efficiency in software development.

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.