Skill UI

A comprehensive strategy for regression testing in AI-assisted development. It focuses on identifying systematic blind spots, such as schema inconsistencies between sandbox and production paths, and integrating automated bug checks into the development workflow. This guide teaches how to build robust, database-free API tests to ensure code quality when AI models contribute to the codebase.

This skill allows for the deterministic re-running of recorded user session paths (trajectories). It is essential for regression testing, bug reproduction, and verifying UI flow consistency after deployments. Crucially, it utilizes browser-selectors embedding similarity to intelligently recover and retry interactions even when the underlying webpage structure (DOM) has drifted, providing robust testing capabilities.

This skill monitors for regressions on deployed URLs following deployments, merges, or dependency upgrades. It performs comprehensive checks including HTTP status, console errors, network failures, performance metrics (LCP/CLS/INP), and crucial API endpoint health, ensuring service stability in production or staging environments. Supports quick checks, continuous monitoring, and differential comparison against baselines.

A comprehensive guide to safe and reversible database migration patterns. Covers zero-downtime schema changes, data backfilling, and rollbacks for major databases like PostgreSQL and MySQL, and popular ORMs (Prisma, Drizzle, Django). Learn techniques like concurrent indexing and the expand-contract pattern to ensure production stability.

This guide outlines the architecture and implementation steps for building a robust, production-ready design system. It covers core elements like design tokens, reusable components, and layout patterns. Ideal for teams needing to maintain design consistency, ensure accessibility, and synchronize design (Figma) with implementation (Storybook).

This guide outlines best practices for building scalable and maintainable Django applications and APIs. It covers recommended project layouts, implementing separated configuration files (dev/prod), advanced ORM techniques, and integrating middlewares, caching, and signals for enterprise-level robustness. Ideal for professional backend development.

A comprehensive guide covering essential security best practices for Django applications. It details how to implement robust authentication, granular authorization (RBAC), and crucial security settings like CSRF/XSS protection, HSTS, and secure environment configuration to prevent common vulnerabilities in production deployments.

A comprehensive, multi-phase checklist for ensuring the quality, security, and deployment readiness of Django applications. It covers linting (ruff, mypy), unit testing (pytest), database migrations, security audits (bandit, pip-audit), and performance checks, making it an essential quality gate for CI/CD pipelines before merging or deploying to production.

This guide outlines architectural patterns and best practices for building scalable, production-ready APIs with FastAPI. It covers proper project structure, separating concerns using routers, services, and CRUD layers, implementing dependency injection for database sessions and authentication, defining Pydantic schemas for request/response, handling asynchronous operations, and managing custom error responses.

A powerful tool for creating professional, animation-rich, and zero-dependency HTML presentations. It supports generating pitch decks, workshop materials, or internal talks from scratch, or converting existing .ppt/.pptx files. The system ensures mandatory viewport fitting, responsiveness across all devices, and includes advanced features like keyboard/touch navigation and reveal animations, resulting in production-quality, modern web presentations.

An expert skill for creating highly optimized, minimal, and fast-starting Windows installers for Python applications. Utilizing advanced techniques like Nuitka's extreme compilation, DLL footprint analysis, and Inno Setup packaging. This process ensures a clean, professional, and resource-efficient deployment, suitable for commercial products, rather than basic script conversion.

This skill helps transform vague product or engineering ideas into structured, verifiable acceptance criteria (AC). It is crucial for high-impact changes involving security, data migration, or external APIs. By inspecting existing context and asking minimal, targeted questions, it produces clear, observable criteria, significantly de-risking the development process and ensuring handoff readiness.