Skill UI

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.

A comprehensive skill designed to manage, track, and persist image assets generated by Ideogram's API. This tool addresses the critical issue of expiring image URLs by implementing a complete lifecycle pipeline. It handles metadata tracking (prompt, seed, model, style, etc.), immediate downloading, and robust storage to both local filesystems and cloud solutions like S3. Features include asset persistence, generation history logging, and image reproduction using stored seed values.

This skill outlines a comprehensive, multi-agent orchestration workflow designed for sophisticated production issue resolution. It systematically combines AI code assistants, observability platforms (like Sentry/DataDog), and automated techniques (e.g., git bisect, distributed tracing) into a rigorous four-phase process: Issue Analysis, Root Cause Investigation, Fix Implementation, and Verification. It guides best practices for reducing Mean Time To Recovery (MTTR) and improving system resilience in complex, multi-system environments.

This skill provides comprehensive support for designing, calibrating, and standardizing entire role-based interview loops and hiring pipelines. It helps users structure competency assessments, generate targeted questions, reduce interviewer bias, and ensure the hiring process is consistent, objective, and aligned with core role competencies. Ideal for HR teams, hiring managers, and talent development professionals.

A comprehensive guide applying Kaizen (continuous improvement) and Poka-Yoke (error proofing) principles to software development. Use this skill when you need to enhance code quality, refactor large systems incrementally, validate designs, or optimize development processes by focusing on prevention rather than fixing bugs.

This is a production-grade reference architecture for building scalable video generation platforms powered by Kling AI. It details the complete pipeline, from the API gateway and job queuing (Redis/SQS) to the worker pool, object storage, and CDN delivery. Use this guide when designing high-throughput, resilient, and scalable AI video systems.

This blueprint provides a scalable, production-grade reference architecture for advanced LLM applications using LangChain. It guides the implementation of layered design, provider abstraction (allowing seamless switching between LLMs like OpenAI and Anthropic), dynamic chain registry, robust RAG pipelines, and complex multi-agent orchestration. Ideal for building enterprise-level, maintainable, and highly flexible AI systems.

A comprehensive diagnostic toolkit designed for advanced troubleshooting of Lindy AI agents. This bundle systematically collects environment information (OS, Python, Node.js), tests API connectivity for webhooks and major integrations (Slack, Notion, Gmail), reviews task history, and guides the user in generating a full, structured support ticket for technical support.