Skill UI

This skill acts as a specialized tutorial engineering specialist, transforming raw, complex technical concepts or codebases into structured, progressive, and engaging educational content. It applies pedagogical design principles, such as progressive disclosure, spaced repetition, and hands-on exercises, to create documentation, courses, and onboarding materials that teach users how to build, debug, and optimize, rather than just referencing information.

Performs pattern-driven searches for similar vulnerabilities across repositories after a known issue is found, guiding analysts through precise generalization, triage, and tool choices (ripgrep, Semgrep, CodeQL) to audit and prioritize true positives.

This skill automatically generates structured and user-friendly changelogs by analyzing the complete git commit history. It groups commits by time period (daily/weekly) and classifies changes into key categories (Features, Fixes, Docs, etc.), providing a concise summary of recent development activity for end-users. Ideal for answering 'what changed recently' or summarizing project updates.

Master the architecture of reliable distributed systems using advanced workflow orchestration patterns. This guide covers fundamental design decisions, including the distinction between Workflows and Activities, and introduces critical patterns like Saga for distributed transactions, Entity Workflows, and Fan-Out/Fan-In. Learn best practices for handling long-running processes, state persistence, and failure recovery to build robust business logic.

Create a disciplined, developer-ready implementation plan whenever a multi-step spec arises; document every file, command, and bite-sized action with precise steps, tests, and commit guidance so any engineer can execute confidently with DRY/YAGNI/TDD practices.

A comprehensive guide for developing, optimizing, and standardizing skills for AI agents. This resource provides a decision tree for choosing the right architecture (Tier 1-3), incorporating best practices like CSO (LLM SEO) and Anti-Rationalization, and ensuring compliance through rigorous testing and checklists. Essential for robust AI system building.

Python framework for multi-objective optimization, offering NSGA-II/III, MOEA/D, benchmark suites, customizable operators, and visualization to help engineering teams explore Pareto fronts and make multi-criteria decisions.

A guide for creating and maintaining the canonical `AGENTS.md` file. This skill enforces minimal, high-signal documentation, ensuring agents receive concise instructions regarding package management, file-scoped commands, and project conventions, while strictly omitting filler or obvious context.

This comprehensive guide helps users build, audit, and debug robust analytics tracking systems using GA4 and Google Tag Manager. It focuses on establishing a consistent event taxonomy and capturing every meaningful user action—from initial visits to complex conversions—ensuring data integrity for accurate decision-making.

Provides a concise reference for shared AWS concepts so teams can standardize commonly used cloud resources, practices, and patterns when building or maintaining infrastructure-heavy projects.

A comprehensive guide detailing best practices for building high-quality, native-feeling applications using Expo Router. It covers advanced topics like component usage, advanced styling (flexbox, gradients), responsiveness, navigation patterns, and critical decisions on whether to use Expo Go or custom native builds.

Scans cryptographic implementations to flag operations whose timing decisions leak secrets, offering language-specific guides, architecture/optimization options, and output modes so teams can enforce constant-time practices across reviews and CI.