Skill UI

Guides Python developers through architecture decisions, framework choices, async vs. sync trade-offs, type-hint strategies, and project structure best practices for 2025 projects.

This guide provides comprehensive patterns for designing and implementing secure multi-tenant SaaS applications using shared databases. It covers critical techniques like Row-Level Security (RLS) in PostgreSQL, implementing tenant-aware middleware in TypeScript (Express/Fastify), and enforcing data scoping at the ORM level (Prisma/Drizzle). Learn how to prevent data leakage and manage tenant isolation across shared schemas.

Guides building Spring Boot apps with layered architecture, REST controllers, JPA repositories, transactional services, global exception handling, DTO mappers, and testing checkpoints.

Summarizes the Test-Driven Development workflow with RED/GREEN/REFACTOR phases, the AAA pattern, prioritization cues, anti-patterns, and AI-augmented agent roles to guide implementation.

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 details how to analyze comprehensive Zeek network logs (conn.log, smb_files.log, ntlm.log, dce_rpc.log, etc.) to detect advanced attacker techniques. It specifically targets indicators of compromise related to lateral movement, such as SMB admin share access, NTLM account spraying, and remote service execution (DCE/RPC patterns). It is a critical network forensics tool for post-incident investigation.

This system detects ransomware by combining multiple advanced techniques: real-time entropy analysis, file system I/O monitoring, and behavioral heuristics. It identifies abnormal mass file modification patterns, sudden spikes in data entropy (indicating encryption), and suspicious process activities like shadow copy deletion. Ideal for building advanced EDR detection layers to catch zero-day and unknown ransomware variants.

A comprehensive, library-agnostic checklist covering best practices for Flutter and Dart applications. It guides developers on architectural principles, state management patterns (BLoC, Riverpod, etc.), Dart idioms, performance optimization, and clean code principles, making it invaluable for code reviews.

A comprehensive guide to professional Git version control. It covers best practices for branching strategies (GitHub Flow, GitFlow, Trunk-Based), writing standardized commit messages using Conventional Commits, managing merges vs. rebases, and defining effective Pull Request workflows. Ideal for any development team looking to improve code collaboration and maintain a clean, traceable history.

This library provides comprehensive patterns for building robust Clinical Decision Support Systems (CDSS) integrated into Electronic Medical Records (EMR). It ensures patient safety by implementing critical checks such as drug interaction screening, weight/age/renal-adjusted dose validation, and standardized clinical scoring (e.g., NEWS2). The engine uses pure functions, guaranteeing high testability and reliability for critical medical insights.

A comprehensive guide detailing architectural patterns for developing robust Electronic Medical Record (EMR) and Electronic Health Record (EHR) systems. Covers critical areas like patient safety protocols, structured clinical workflows, drug interaction checking, audit trail implementation, and WCAG accessibility standards. Essential for building highly reliable and compliant healthcare IT solutions.

A comprehensive guide to building HIPAA, GDPR, and other global compliance systems for healthcare applications. This pattern outlines best practices for protecting Protected Health Information (PHI) and Personally Identifiable Information (PII) by implementing robust access controls, Row-Level Security (RLS), and mandatory audit trails. Essential for any feature handling patient or clinical data.