Skill UI

This skill enables comprehensive security graph mapping by ingesting both on-premises Active Directory data (via SharpHound) and cloud Entra ID data (via AzureHound) into BloodHound CE. It analyzes complex, hybrid attack paths, allowing security teams to identify critical privilege escalation chains from low-privileged accounts to Tier-0 assets, mapping findings to MITRE ATT&CK.

This PowerShell toolset performs advanced post-exploitation, reconnaissance, persistence, and data exfiltration against Microsoft 365/Entra ID tenants using the Microsoft Graph API. It operationalizes stolen Graph tokens to enumerate users, dump policies, escalate privileges, and search sensitive data across mailboxes, SharePoint, and Teams. Essential for authorized red teaming engagements.

This comprehensive tool performs an architectural audit of a codebase, mapping module dependencies, checking layering integrity, and flagging structural decay. Drawing on classic engineering principles (like Conway's Law and Testability Seams), it provides a deep assessment of the project's health and structure. Ideal for large-scale code reviews or onboarding new developers.

This skill provides a comprehensive set of core UI components (e.g., Box, Button, Input, Card) and implements a structured design system. It guides developers on using design tokens (like `$textPrimary` or `$4`) instead of hard-coded values, ensuring visual consistency and scalability across applications. Ideal for any project requiring standardized, maintainable UI development.

A comprehensive resource containing official, managed integration examples for popular third-party services (Stripe, OpenAI, Supabase, etc.). This library provides canonical patterns for connecting external APIs into an Expo application. Users can utilize it in two primary ways: adapting the pattern into an existing project (most common) or scaffolding a new greenfield application.

This skill defines a framework-agnostic, scalable architecture pattern for React and React Native applications. It mandates feature modules, strict state separation (server vs. UI), and disciplined import rules to create predictable, maintainable, and highly scalable codebases, regardless of the chosen framework (Next.js, Remix, etc.).

This skill manages the end-to-end lifecycle of cloud test execution using HyperExecute for platforms like LambdaTest/TestMu AI. It provides comprehensive functionality to analyze projects, generate and validate complex YAML configurations, run CLI jobs, and debug failures. Ideal for integrating robust, scalable, and matrix-based testing into CI/CD pipelines.

This skill helps generate comprehensive and structured TestNG test cases for Java. It supports advanced testing features crucial for enterprise automation, including method grouping, data-driven testing using @DataProvider, parallel execution setup, XML suite configuration, and custom listeners. Use it when building robust, scalable, and maintainable automated test suites.

This skill systematically scans Apple's comprehensive developer documentation, specifically targeting SwiftUI. It identifies deprecated APIs, finds their modern replacements, and updates the expert skill's reference guide. Use this when required to refresh deprecated features, check for new API deprecations after an iOS/Xcode update, or maintain the most current best practices for SwiftUI development.

A comprehensive guide detailing industry-standard best practices for building scalable and maintainable Flutter/Dart applications. This skill covers architectural patterns (MVVM, feature-based design), state management, coding standards (modern Dart features, widget usage), and testing methodologies. Use it for planning, structuring new features, reviewing existing codebases, or refactoring complex logic into robust, testable components.

The Agent Harness provides a robust, verifiable loop structure for driving complex goals across specialized domains. It converts a high-level objective into a verifiable task plan, executes tasks sequentially using domain-specific tools, and rigorously verifies every step with machine-run checks. The system includes mechanisms for retries, budget management, and mandatory human escalation, ensuring no goal is closed until all progress is verifiably complete or explicitly waived.

This skill guides the safe, systematic, and at-scale refactoring of existing Go codebases. It ensures that structural changes maintain observable behavior by following a rigorous process: mapping blast radius, strengthening safety nets (tests), applying small tool-driven transforms, and committing changes atomically via staged PRs. Ideal for cleaning up large functions, resolving code smells, renaming packages, or tackling complex architectural improvements in Go.