Skill UI

This skill provides a comprehensive, structured workflow for diagnosing performance bottlenecks in SwiftUI applications. It guides users through a code-first review to detect common issues like invalidation storms, layout thrash, or heavy main-thread work. When code review is insufficient, it provides detailed guidance on collecting runtime evidence using Instruments, enabling precise root cause analysis and targeted remediation strategies.

A comprehensive guide detailing proven patterns for building robust and scalable SwiftUI applications. Covers modern state management (@State, @Observable), advanced navigation (Sheets, NavigationStack), handling asynchronous data flows, and adhering to architectural best practices to create maintainable, performant UIs.

A comprehensive guide detailing how to refactor large, complex SwiftUI views into smaller, more stable, and explicit components. It emphasizes adopting a lightweight state approach (favoring local state and environment variables over excessive view model layers) to improve data flow, readability, and overall code maintainability in modern iOS development.

A comprehensive guide detailing best practices for executing commands on Windows using PowerShell and CMD. It addresses critical pitfalls such as handling spaces in file paths, ensuring correct character encoding (UTF-8), using native cmdlets, and managing long path limits. Essential for developers building robust, cross-platform Windows automation scripts.

A comprehensive tool for generating publication-quality figures essential for Machine Learning and AI academic papers. It supports two distinct workflows: generating complex system architecture and workflow diagrams using AI (Gemini), and creating precise, data-driven visualizations (line charts, heatmaps, etc.) using standard libraries like matplotlib and seaborn. Use it when preparing any figure for a conference submission.

A comprehensive guide to designing scalable, cost-effective, and compliant architectures on Microsoft Azure. This skill covers the entire lifecycle, from gathering detailed business requirements (SLA, RPO/RTO) and selecting appropriate service patterns (AKS, Serverless, Data Factory), to generating Infrastructure as Code (IaC) using Bicep. It also includes steps for cost optimization, reserved instance planning, and setting up robust CI/CD pipelines via Azure DevOps or GitHub Actions.

This comprehensive workflow guides the design, optimization, and deployment of scalable, cost-effective Google Cloud Platform (GCP) architectures for both startups and large enterprises. It covers the full lifecycle, from gathering detailed requirements (compliance, SLA) and recommending optimal patterns (Serverless, GKE, Data Pipelines) to estimating costs, generating Infrastructure as Code (IaC) using Terraform, setting up CI/CD pipelines, and completing a thorough security review.

A comprehensive guide to advanced development practices on the Snowflake platform. Covers best practices for SQL (MERGE, semi-structured data, colon prefix rule), modern data pipeline construction (Dynamic Tables, Streams/Tasks, Snowpipe), and deep integration with Cortex AI functions and Snowpark Python. Essential knowledge for data engineers building robust, scalable, and intelligent data applications.

A comprehensive guide for preparing SaaS and cloud infrastructure companies for SOC 2 Type I and Type II audits. Covers mapping Trust Service Criteria (TSC), generating control matrices, performing thorough gap analysis, collecting evidence, and assessing overall compliance readiness across Security, Availability, Confidentiality, and Privacy domains. Essential for demonstrating operational trustworthiness to enterprise clients.

This guide enforces the 'spec-first' principle in software development, treating the specification as a non-negotiable contract. It outlines a rigorous, multi-stage workflow detailing mandatory sections (Functional/Non-Functional Requirements, Acceptance Criteria, API Contracts, Data Models) and bounded autonomy rules. Users learn how to define the system 'must do' before writing a single line of code, thereby minimizing rework and eliminating scope creep.

A powerful operational companion for database developers. This skill assists with the daily lifecycle of database interactions, including translating natural language requirements into optimized SQL queries, generating database migrations, performing comprehensive schema introspection across multiple dialects (PostgreSQL, MySQL, SQLite, SQL Server), and identifying performance bottlenecks through detailed query optimization and index recommendations. It also supports ORM patterns like Prisma and SQLAlchemy.

AKF is the native metadata format specifically designed for tracking AI-generated or AI-modified content. It allows users to stamp files (including DOCX, PDF, images, and code) with detailed trust scores, source provenance, and compliance metadata. This tool is essential for professional workflows requiring strict auditing, compliance assurance, and verifiable data lineage, especially concerning regulations like the EU AI Act, HIPAA, and SOX.