Skill UI

This skill provides comprehensive guidance on optimizing Guidewire application performance. It covers advanced development techniques such as optimizing Gosu queries using the Query API, implementing efficient batch processing with BatchProcessBase, implementing caching strategies for frequently accessed reference data, and performing JVM heap tuning via the Guidewire Cloud Console (GCC). Use this when system performance bottlenecks are detected in Guidewire insurance or core business platforms.

This skill provides comprehensive guidance and tools for managing rate limits, quotas, and throttling when integrating with the Guidewire Cloud API. It is essential for high-volume, mission-critical integrations, advising on best practices like implementing exponential backoff for 429 responses and optimizing batch operations using bulk endpoints to ensure system stability and throughput.

This document provides the enterprise reference architecture for deploying Guidewire InsuranceSuite Cloud. It details the integration flow from the Jutro Frontend through the Cloud API Gateway to core modules like PolicyCenter, ClaimCenter, and BillingCenter. It guides users on the overall system structure, data warehousing via DataHub, and analytics using Explore.

This guide outlines critical security measures for integrating with Guidewire systems, which handle sensitive policyholder PII, claims, and financial data. It covers best practices for implementing OAuth2 JWT authentication, API role scoping, input validation, and sensitive data redaction (PII) to prevent data breaches and meet compliance standards.

A specialized AI assistant acting as an expert Haskell engineer. This skill focuses on advanced type systems (GADTs, type families), pure functional architecture, concurrency (STM, async), and high-assurance software design. Use it for building robust, idiomatic, and maintainable Haskell code.

Provides comprehensive guidance on implementing standard user interface controls according to Apple's Human Interface Guidelines (HIG). It details the appropriate use cases for toggles, segmented controls, pickers, sliders, and other input elements, ensuring designs are consistent, accessible, and optimized for the Apple ecosystem.

A comprehensive guide detailing Apple's Human Interface Guidelines (HIG) for integrating apps into system surfaces. Covers best practices for widgets, Live Activities, notifications, complications, App Clips, and other system components, ensuring apps provide glanceable, contextual utility outside the main app environment.

A comprehensive guide detailing the core principles of Apple's Human Interface Guidelines (HIG). It covers essential topics such as accessibility (VoiceOver, Dynamic Type), utilizing system colors and materials, adhering to platform conventions, and best practices for typography, layout, and motion. Use this guide to ensure your application design is native, inclusive, and highly polished across all Apple operating systems.

Provides comprehensive best practices for designing user interfaces that support diverse input methods across the Apple ecosystem. This guide covers everything from standard gestures, Apple Pencil interactions, keyboard shortcuts, to specialized inputs like the Digital Crown, eye tracking, and motion sensors, ensuring cross-platform consistency and optimal user experience.

A comprehensive guide for designing cross-device applications across the Apple ecosystem. This skill helps developers adhere to the specific Human Interface Guidelines (HIG) for various platforms—including iOS, macOS, watchOS, tvOS, and visionOS. It emphasizes adapting design principles (e.g., touch-first vs. pointer-based vs. spatial) while maintaining brand consistency, ensuring a native and optimal user experience regardless of the operating system.

This skill automatically gathers and structures comprehensive context for Apple product development. It analyzes existing project files (like README, Info.plist, and code) and prompts the user for details across product overview, target platforms, technology stack, design system, and accessibility requirements. The output is a structured context document used by other specialized skills to ensure consistent, informed design and development decisions.

Provides a comprehensive guide and Python implementation for creating container-based hosted agents in Azure AI Projects. It utilizes ImageBasedHostedAgentDefinition to define the agent's container image, required resources (CPU/memory), supported tools, and communication protocols. Essential for deploying robust, production-ready AI agents within the Azure ecosystem.