Skill UI

KAPE is a powerful, Windows-native triage tool used for Digital Forensics and Incident Response (DFIR). It executes in two phases: 'Targets' collect raw forensic artifacts (like registry hives, event logs, and prefetch files) from live systems, while 'Modules' parse this collected data into normalized, analyst-ready CSV/JSON formats. It enables fast, defensible, and scalable artifact collection, especially when full disk imaging is impractical.

This comprehensive skill provides a holistic approach to building modern, accessible, and visually stunning user interfaces. It combines the highly accessible components of shadcn/ui (built on Radix UI), the utility-first power of Tailwind CSS, and sophisticated visual design principles (Canvas). Use this when developing complex React applications, implementing full design systems, ensuring responsive layouts across devices, and requiring professional-grade visual compositions, from dashboards to marketing posters. It guarantees consistency, accessibility, and rapid prototyping.

A specialized diagnostic skill designed to analyze failing GitHub Actions workflow logs. It identifies the root cause of crashes, such as missing secrets, environment mismatches, or deprecated syntax. The output provides precise YAML or code diffs required to fix the pipeline and optimize CI/CD processes.

Provides comprehensive architectural guidelines and code patterns for developing high-end, immersive 3D web experiences. This skill covers advanced topics such as custom WebGL shaders, post-processing effects (Bloom, Depth of Field), realistic physics interactions, and crucial performance optimization techniques, ensuring a premium, polished user experience across devices.

This advanced protocol forces the AI to conduct a thorough context audit before attempting any complex task. It mandates reading every relevant file, identifying architectural gaps, and providing a detailed orientation statement. It is essential for multi-file modifications, system design, and debugging to prevent acting on assumptions and maintain high code accuracy. The AI cannot proceed until all unknown variables are resolved.