Skill UI

A comprehensive guide detailing idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and highly maintainable Kotlin applications. Topics include null safety, immutability, sealed classes, structured concurrency, and type-safe DSL builders.

A comprehensive design specification detailing 98 rules for building Command Line Interface (CLI) tools that are safe, reliable, and easily consumable by AI agents. It covers structured JSON output formats, standardized error handling (to stderr), robust input contracts, safety guardrails (e.g., preventing path traversal), and tiered compliance levels (Agent-Friendly, Agent-Ready, Agent-Native) for seamless integration into AI workflows.

Provides a structured, risk-based framework for managing patches in Operational Technology (OT) and Industrial Control Systems (ICS). It addresses the critical difference between IT and OT environments, prioritizing safety and availability over immediate remediation. The guide covers risk scoring, vendor compatibility testing, staged deployment, and defining compensating controls for unpatchable assets.

tRPC allows developers to build highly type-safe APIs in a full-stack environment without needing to write or maintain separate schemas. It provides end-to-end type safety from server routers to client components, supporting queries, mutations, subscriptions, and robust middleware. Ideal for building modern TypeScript monorepos, Next.js, or Remix applications.

A comprehensive guide covering best practices for building and debugging Nuxt 4 applications. It details patterns for ensuring hydration safety, optimizing data fetching with `useFetch` and `useAsyncData`, managing complex routing rules, and implementing lazy loading for superior performance across SSR and client-side environments.

This expert reviews and rectifies complex Swift Concurrency issues, such as actor isolation violations, Sendable safety breaches, and data races. It applies modern patterns (like `@MainActor` and `actor` usage) to ensure code adheres to Swift 6.2+ standards while minimizing behavior changes. Use it when debugging concurrency warnings or migrating legacy codebases.

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.

An automated verification system designed for critical healthcare application deployments (EMR/EHR). This harness enforces stringent patient safety standards by running multiple mandatory test gates, including Clinical Decision Support System (CDSS) accuracy, Protected Health Information (PHI) leakage prevention, and data integrity checks. A single failure in critical gates automatically blocks deployment, ensuring regulatory compliance and optimal patient safety in the CI/CD pipeline.

This framework implements robust guardrails for LLM applications, validating both user inputs and model outputs. It detects prompt injection, sensitive PII (Personally Identifiable Information), toxic content, and ensures structured output compliance using advanced tools like NVIDIA NeMo Guardrails and Guardrails AI. Essential for building secure, reliable chatbots and RAG systems.

This comprehensive guide dives deep into the internals of Go's built-in data structures (slices, maps, arrays) and standard library packages. It covers critical topics like capacity growth mechanics, preallocation strategies, pointer types (unsafe/weak), and the optimized usage of specialized containers (heap, list, ring). Use this resource to select the correct structure for optimal performance and memory safety in expert Go development.

This skill guides developers in writing robust and defensive Go code. It addresses common pitfalls that lead to runtime panics and silent data corruption, such as nil map writes, slice backing array aliasing, silent numeric truncation (int64 to int32), and inaccurate float comparisons. Use this when designing highly reliable Go systems that must withstand typical programmer errors and maintain data integrity.

Creates a new Google Model Armor template via `gws modelarmor +create-template`, requiring project, location, and template ID, with optional preset or JSON payload; aimed at bootstrapping safety filters before sanitization commands.