Skill UI

Runs a Lighthouse-based audit that combines performance, accessibility, SEO, and best-practice checks, categorizes issues by severity, and recommends targeted fixes for requested site reviews.

Guides writing high-quality YARA-X detection rules for malware hunting, covering naming conventions, string selection, performance tuning, migrations from legacy YARA, and reducing false positives when authoring, reviewing, or debugging signatures.

A comprehensive tool for generating, iterating, and scaling high-performing ad copy across major paid advertising platforms (Meta, Google, LinkedIn, etc.). Use this skill when you need to develop ad headlines, body copy, or creative variations, optimizing content based on funnel stage (Awareness, Consideration, Decision) and existing performance data to maximize conversion rates and pass platform reviews.

A specialized review tool for identifying critical performance bottlenecks within Django applications. It focuses on validating issues such as N+1 queries, unbounded querysets, missing database indexes, and write loops. Use this when you suspect database slowdowns or memory exhaustion due to inefficient ORM usage, ensuring findings are provable and actionable.

This skill guides the process of auditing and correcting critical HTML metadata elements, ensuring optimal performance for search engines and social media sharing. It covers page titles, meta descriptions, canonical URLs, Open Graph tags, Twitter cards, favicons, JSON-LD structured data, and robots directives. Use this when implementing or refining SEO metadata, fixing broken social previews, or setting up structured data.

This skill aggregates a user's entire year's work—including GitHub PRs, Notion documents, and Linear tickets—into a single, structured Notion document. It automatically groups these artifacts by project, providing a comprehensive and organized summary ideal for professional reviews or annual performance documentation (e.g., SRED preparation).

A powerful code review utility designed for SwiftUI projects. It comprehensively analyzes code quality, ensuring adherence to modern Swift APIs, optimal performance, robust data flow management, and compliance with Apple's Human Interface Guidelines and accessibility standards (like VoiceOver and Dynamic Type). Use this tool when writing, refactoring, or reviewing complex SwiftUI implementations to maintain high code hygiene and maintainability.

This skill guides the creation of world-class, immersive web designs, aiming for Awwwards-level quality. It emphasizes intentional typography, purposeful motion, and sophisticated visual composition. Users can leverage the detailed scoring rubric (Typography, Composition, Motion, etc.) to review and elevate existing designs, ensuring every pixel is deliberate and performance-optimized.

A comprehensive guide for building or reviewing SwiftUI User Interfaces that utilize the modern Liquid Glass aesthetic. This skill focuses on correctly implementing native Apple APIs (like `glassEffect` and `GlassEffectContainer`) while ensuring proper fallback mechanisms, modifier ordering, and performance for iOS 26+ devices. Ideal for adopting cutting-edge iOS design patterns.

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, library-agnostic checklist covering best practices for Flutter and Dart applications. It guides developers on architectural principles, state management patterns (BLoC, Riverpod, etc.), Dart idioms, performance optimization, and clean code principles, making it invaluable for code reviews.

This framework provides a rigorous, multi-dimensional guide for conducting code reviews. It evaluates five critical axes: correctness, readability, architecture, security, and performance. Use this process before merging any code change, especially when reviewing PRs, refactoring, or evaluating code produced by AI agents, to ensure continuous improvement and maintain high code health.