Skill UI

Specializing in building high-performance, cloud-native applications using C# and the latest .NET 8+ framework. This skill covers end-to-end development, including building robust RESTful APIs (Minimal/Controller), implementing data access with Entity Framework Core, structuring code using CQRS/MediatR, and scaffolding Blazor components. Focuses on modern best practices like async/await, DTO mapping, and proper error handling.

This expert provides advanced, practical knowledge across the entire lifecycle of containerized applications. Core expertise includes multi-stage Dockerfile optimization, container security hardening (non-root users, minimal attack surface), and advanced orchestration using patterns like Docker Compose. Ideal for ensuring robust, secure, and production-ready deployments.

This resource provides a minimal working example for implementing a complete digital document signing workflow using the Documenso SDK. It comprehensively guides users through creating a document, uploading a PDF file, adding designated recipients, placing specific signature fields, and finally triggering the signing process via code examples (TypeScript, Python) or REST API calls. Use this when integrating document signing into new applications or testing core document management capabilities.

Formal evaluation framework for Claude Code sessions that applies evaluation-driven development to define capability and regression checks, run deterministic and model graders, and track pass@k/pass^k reliability metrics before shipping.

This skill provides a comprehensive guide to setting up Continuous Integration and Continuous Deployment (CI/CD) pipelines for applications integrating with Evernote. It covers advanced topics such as creating mock clients for deterministic unit testing, managing sandbox integration tests using GitHub Secrets, and structuring robust automated deployment workflows. Use this when ensuring code quality and reliable deployment for Evernote-based SaaS products.

A comprehensive guide to boosting Evernote API integration performance and scalability. Techniques covered include implementing response caching (using Redis), performing metadata-only queries to minimize data transfer, batching multiple operations, and optimizing client connection management. Essential for building high-performance, reliable applications.

Provides comprehensive strategies and code examples for managing API rate limits when integrating with the Evernote platform. Techniques include implementing exponential backoff, wrapping clients with minimum delays, batching operations, and optimizing queries (e.g., using metadata only) to ensure robust, high-throughput, and stable API usage.

This skill guides the end-to-end development, deployment, and secure integration of complex AI features into Firebase applications. It covers setting up Cloud Functions, Firestore/Storage rules, Authentication, and connecting robustly with Vertex AI/Gemini for advanced AI capabilities. Focuses on building production-grade, highly secure, data-intensive AI systems.

This skill guide is essential for building advanced applications using Gemini and Gemma 4 hosted models. It covers working with multimodal content (text, images, audio, video), implementing complex features like function calling and structured output. It provides up-to-date SDK usage examples for Python, JavaScript, Go, and Java, ensuring developers use the latest, recommended API standards.

This comprehensive guide provides strategies to optimize your Granola spending. Learn how to calculate individual and team ROI by quantifying time saved, selecting the most appropriate plan (Basic, Business, or Enterprise) based on usage needs, auditing inactive seats, and implementing advanced billing strategies to maximize value and minimize costs.

A comprehensive guide to the Apple Human Interface Guidelines (HIG), detailing best practices for designing seamless and intuitive user experiences across various interaction scenarios. It covers key principles such as minimizing modality, providing clear feedback, handling data entry, progressive onboarding, and managing complex features like sharing and drag-and-drop, ensuring your application feels native and polished.

Provides comprehensive strategies to optimize Langfuse tracing overhead for high-throughput applications. This guide covers benchmarking, tuning batch processing configurations, implementing non-blocking wrappers, and optimizing payload sizes. Use this when scaling Langfuse for production workloads to minimize latency and maximize stability.