Skill UI

This skill guides you in implementing Command Query Responsibility Segregation (CQRS) patterns for scalable software architectures. It focuses on separating read and write models to optimize query performance and support event-sourced systems. Use this when you need to scale reads independently from writes or handle complex query scenarios. It is suitable for building high-performance reporting systems where detailed read/write data models are required.

Reference patterns for building AI agents that autonomously discover, score, and acquire token listings for crypto exchanges, including wallet forensics and outreach pipelines.

Provides comprehensive C# development guidelines covering LINQ, null handling, async/await, records, error handling, and resource management. Promotes idiomatic, efficient, and secure coding patterns while avoiding common anti-patterns for better code quality.

Generate production-grade Cypress E2E and component tests in JavaScript or TypeScript. Supports local execution and TestMu AI cloud for cross-browser testing. Includes patterns for command chaining, selectors, network interception, and custom commands to ensure reliable automation.

This skill provides comprehensive guidelines for writing idiomatic and efficient Dart code. It covers null safety, collections, classes, async/await patterns, error handling, and Flutter-specific best practices. Use it to improve code quality and maintainability in Dart projects.

A design and implementation guide for professional interfaces that maximize information density, with compact layouts and tabular data patterns for web, SwiftUI, and Flutter apps.

A guide to production-ready patterns for dbt (data build tool). It covers essential practices for robust data pipeline development, including model organization (staging, intermediate, marts), implementing advanced testing strategies, ensuring data quality, and optimizing incremental processing for large datasets.

This skill guides the definition of relationships and integration contracts between distinct bounded contexts within a complex system using Domain-Driven Design (DDD) patterns. It is crucial for preventing domain leakage, planning anti-corruption layers (ACLs), and clarifying ownership boundaries when multiple services interact, ensuring a robust and scalable system architecture.

This skill helps developers apply Domain-Driven Design tactical patterns to structure code effectively. It involves using entities, value objects, aggregates, repositories, and domain events to enforce explicit invariants. Use this when translating domain rules into code structures or refactoring anemic models. It focuses on design boundaries and behavior-rich objects rather than strategic boundaries or deployment architecture.

This skill detects and removes AI-generated patterns in Chinese text using a 35-pattern catalog. It calculates an AI-smell index to diagnose machine-written content, rewrites drafts to sound human, and supports style cloning. Ideal for marketing copy, articles, and social posts where natural tone is required.

This skill focuses on spatial composition in UI design. It emphasizes rendering and judging visual output rather than relying solely on code tokens. It helps avoid generic AI design patterns and ensures layouts do not have horizontal overflow. Key practices include using fresh eyes to critique, avoiding fixed style prescriptions, and strictly checking scrollWidth to prevent layout failures. It guides developers to prioritize process over look and ensures responsive design integrity.

Provides practical DevOps deployment patterns for Docker, CI/CD with GitHub Actions, AWS Lambda/SAM, Terraform, infrastructure as code, health checks, rollback, and monitoring.