Coding standards, frameworks, refactoring, and code review (16.7K skills)
Build web interfaces that adapt to screen and component widths. Use CSS Grid, flexible text and spacing, and container queries, which respond to a component’s available space, to adjust layouts, images, navigation, and tables.
Build Stripe payment flows for one-time purchases and subscriptions. The skill covers checkout options, customer payment methods, refunds, and webhooks, which notify an application about payment events, with examples for testing payment behavior.
Turn Python code into installable libraries or command-line tools. The skill guides project structure, package metadata, dependency settings, building wheel and source archives, and publishing releases to PyPI or private package repositories.
Integrate PayPal into online checkout flows with one-time payments, subscriptions, refunds, and payment notifications. Includes client-side buttons, server-side payment handling, and sandbox testing to check the purchase flow before using live credentials.
Add Python type hints and configure strict checking with mypy or pyright to catch type errors before execution. Covers reusable classes that preserve type information, interfaces defined by required members, and checks for possibly missing values.
Implement Python error handling with early input checks, appropriate exception types, and clear messages. Handle individual failures in batch jobs, preserve error context for debugging, and use Pydantic models to validate structured input.
Measure Python execution time and memory use to locate slow or resource-heavy code. Use profiling results to guide improvements in data structures, caching, input and output operations, algorithms, and parallel processing.
Review Python code for common mistakes in error handling, asynchronous operations, type annotations, and tests. Use a practical checklist and correction examples to guide code reviews, investigate bugs, and improve existing implementations.
Design and refactor Python components with clear responsibilities and simple structure. Assess when to split large classes, combine objects instead of extending them, and extract shared code without introducing unnecessary abstractions.
Organize Python projects with clear file responsibilities, directory layouts, and public interfaces—the functions and classes intended for other code to use. Covers new projects, existing code reorganization, test placement, package exports, and dependency direction.
Move Python application settings out of code and into environment variables. Use pydantic-settings to check value types and required fields at startup, organize development and production settings, and keep secrets out of version control.
Add retries and timeouts to Python service calls, with increasing and randomized waits between attempts. Use examples to distinguish temporary failures from permanent errors, limit retry duration, and record retries in logs.
Set consistent Python conventions for naming, formatting, type checking, and documentation. Configure ruff and mypy or pyright, write clear function descriptions, and organize README and changelog content so a team can maintain shared standards.
Move slow Python operations into background jobs so requests can return promptly. Use task queues and workers, the processes that execute queued work, with retry rules, duplicate handling, time limits, and persistent job status.
Structure Python code to release files and database connections reliably, including when errors occur. Covers context managers, which handle setup and cleanup, asynchronous resources, nested cleanup, and streaming responses that retain accumulated state.
Help implement automated subscription billing, invoice generation and delivery, and recovery of failed payments. Cover subscription states, renewals, usage-based charges, prorated plan changes, and tax calculations as parts of the billing workflow.
Set up Python projects with uv, manage required packages, and create isolated environments for each project. Covers Python versions, dependency updates, migration from existing tools, and lockfiles that record package versions for repeatable installations.
Build Python applications that handle other work while waiting for network or database operations. Use asyncio and async/await to run tasks concurrently, manage errors and timeouts, and handle cancellation with appropriate cleanup.
Analyze compiled programs without running them by recognizing branches, loops, data structures, and common instruction patterns. Use disassembly and decompilation, which translate machine code into readable representations, to reconstruct program logic and document findings.
Build and review C#/.NET APIs and business backends using concrete implementation patterns. Cover asynchronous operations, service dependencies, database access, configuration, caching, and tests to structure application code and examine quality and performance issues.
Refactor JavaScript using ES6+ features to make code easier to read and maintain. Covers asynchronous operations with async/await, modules, and functional patterns that transform data without changing the original values.
Choose and implement ways to manage data in React apps, from values held by individual components to shared data and cached server responses. Covers Redux Toolkit, Zustand, Jotai, and React Query, including migration from legacy Redux.
Helps plan and implement database structure changes and data transformations using Sequelize, TypeORM, or Prisma. Includes staged changes intended to avoid downtime, plus transaction and backup examples for rolling back failed migrations.
Build workflows that generate changelogs and release notes from commits, pull requests, and releases. Use Keep a Changelog formatting, standardize commit messages with Conventional Commits, and manage version numbers through Semantic Versioning rules.