Skill UI

This comprehensive guide details the idiomatic and efficient way to write Scala code. It covers crucial modern practices, such as utilizing functional transforms over traditional loops, embracing pattern matching, using Option/Either for robust error handling instead of null checks or exceptions, and managing concurrency safely. Essential reading for any Scala developer aiming for high-quality, maintainable, and performant codebases.

A comprehensive guide covering modern Swift best practices. Learn how to handle optionals safely, utilize functional transforms, manage concurrency with async/await, and adopt Protocol-Oriented Programming (POP). This reference helps developers write highly performant, idiomatic, and safe Swift applications.

A comprehensive guide detailing modern, idiomatic, and efficient patterns for TypeScript and JavaScript development. It covers essential best practices from array manipulation (map, reduce) and destructuring to advanced asynchronous handling (async/await, Promise.all) and type safety best practices, helping developers write cleaner, more robust, and performant code.

This tool conducts structured reviews of various Infrastructure-as-Code (IaC) tools (e.g., Terraform, Pulumi) across multiple cloud providers. It generates an actionable report that categorizes findings by severity (Critical, High, Medium, Low), providing detailed remediation steps and a reusable best-practice checklist for continuous security, compliance, and operational auditing.

Master the end-to-end process of creating Power BI paginated reports using the RDL format. This skill provides guidance on developing print-faithful, multi-page documents like invoices and statements. It covers initial requirements interviews, understanding the core RDL XML structure, best practices for validation, and the critical final rendering and publishing steps in the Power BI Service or Fabric.

A comprehensive red-teaming skill for assessing the security posture of Retrieval-Augmented Generation (RAG) pipelines. It systematically probes two critical injection surfaces: poisoned retrieved context (indirect prompt injection) and embedding manipulation. Use this skill to validate retrieval guardrails, ensure data leak prevention, and demonstrate vulnerabilities in LLM-powered knowledge assistants.

This skill validates the correctness and completeness of any API request. It rigorously checks the HTTP method, URL structure, required headers, body format, authentication details, and query parameters. Use it to debug cURL commands, verify endpoint calls, or ensure API structures adhere to best practices, providing immediate, actionable feedback on required fixes.

This skill generates robust, production-grade Appium automation scripts for both Android and iOS. It supports multiple languages (Java, Python, JavaScript) and guides users through best practices for cross-platform testing, including proper locator strategies, explicit waiting, and complex gestures. Ideal for automating mobile QA processes on local emulators or cloud real device farms.

This skill provides comprehensive best practices for designing modern and robust React user interfaces. It covers critical patterns for managing asynchronous data, including optimal loading state indicators (skeletons vs. spinners), structured error handling hierarchies, and designing contextual empty states. Essential for improving user experience during data fetching and operations.

This guide details advanced strategies for publishing technical content across major developer platforms like Dev.to and Hashnode. It covers cross-posting best practices, canonical URL management for optimal SEO, and platform-specific optimization (e.g., tagging, content performance) to maximize reach and build authority.

A portable, framework-agnostic system designed for robust field-side observability in React or React Native apps. It establishes a strongly typed event taxonomy, ensures best-effort, non-blocking data fan-out across multiple analytics providers, and enforces consent gates for all telemetry data. This system complements synthetic testing by capturing real user vitals (LCP, INP, CLS) and behavioral events in production.

This guide details best practices for implementing robust, type-safe GraphQL queries and mutations. It covers using separate .gql files, running code generation tools, and implementing mandatory error handling (onError) and loading states. Use this when building complex, reliable data fetching layers with Apollo Client.