Skill UI

A comprehensive guide detailing Apple's Human Interface Guidelines (HIG) for implementing essential UI status components. Covers best practices for progress indicators (determinate vs. indeterminate), status bars, and activity rings across iOS and watchOS. Essential for developers ensuring native, platform-compliant, and user-friendly status feedback.

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.

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.

This comprehensive guide outlines Apple's Human Interface Guidelines (HIG) for various technologies and user flows (e.g., Siri, Apple Pay, HealthKit, ARKit, Generative AI). It teaches developers how to ensure their applications feel natively integrated, respect user privacy, and adhere to established platform patterns across iOS, macOS, and other Apple devices. Essential reading for building high-quality, compliant, and seamless user experiences.

This skill leverages Google Gemini's advanced image generation model to create high-quality, context-specific visuals. It is essential for developers needing placeholder images for UIs, generating detailed diagrams for technical documentation, or visualizing abstract concepts, logos, and assets across cross-platform projects (Windows, macOS, Linux).

Generates and implements backup strategies for databases and applications, producing configuration files and automation scripts that ensure secure, scalable protection and disaster recovery readiness across platforms.

This guide details the setup and management of the Juicebox AI platform across multiple isolated environments: Development, Staging, and Production. It ensures workspace isolation, controls data access, and maintains data integrity by differentiating sample datasets (Dev), full datasets with restricted exports (Staging), and full-featured production environments. Follow this workflow to safely deploy and test analyses from development to live production.

Provides deep expertise in modern Kotlin patterns, covering structured concurrency via Coroutines and Flow, Multiplatform architecture (KMP), declarative UI using Compose, and server implementation with Ktor. Ideal for building robust, type-safe, and highly maintainable applications across various platforms.

Consolidates Kubernetes deployment best practices across manifests, Helm charts, autoscaling, and troubleshooting to keep API workloads resilient, efficient, and observable. Ideal for SREs or platform teams standardizing resource limits, probes, topology spread, and diagnostics.

A comprehensive guide for deploying the application layer that interacts with Lindy AI agents. This includes setting up webhook receivers, managing callback handlers, and ensuring production readiness across multiple platforms like Docker, Vercel, and AWS. It covers prerequisites, multi-step deployment instructions, post-deployment verification scripts, and rollback plans for robust MLOps practices.

This comprehensive guide details the deployment process for Mistral AI-powered applications across various cloud and container platforms, including Vercel, Docker, Google Cloud Run, and self-hosted vLLM setups. It covers secure API key management, platform-specific secret configuration, and the full steps required to establish robust, scalable production pipelines for your AI model.

Mastery of modern mobile development across multiple platforms, including React Native, Flutter, and native iOS/Android. Expertise covers the entire lifecycle, specializing in architectural patterns (Clean, MVVM), performance optimization, offline-first data synchronization (GraphQL, SQLite), advanced DevOps practices (CI/CD, Fastlane), and App Store Optimization (ASO). Ideal for building robust, scalable, and highly performant cross-platform applications.