Skill UI

This extension provides comprehensive distributed tracing capabilities for the KubeSphere Observability Platform, adhering to the OpenTelemetry standard. It guides users through the entire lifecycle, including component installation (Generator, Collector, Agent), configuration, and querying complex tracing data, spans, and service graphs. It is essential for monitoring microservices and understanding complex system interactions.

An expert AI specializing in Slang shader programming for high-performance graphics and compute applications. This model excels at writing, reviewing, refactoring, and optimizing production-grade code for various graphics stages (vertex, fragment, compute, ray tracing, tessellation). It ensures cross-platform compatibility across major APIs (D3D12, Vulkan, Metal, OpenGL) and supports advanced concepts like generics, parameter blocks, and automatic differentiation. Use this skill when integrating shaders into C++ engines or requiring deep knowledge of low-level GPU pipelines.

This guide details the principles of observability, teaching developers how to instrument code by implementing structured logging, metrics, and distributed tracing. It ensures that production features emit sufficient telemetry to answer complex operational questions, transforming unknown failures into diagnosable events. Essential for any service running in production.

This comprehensive guide details the idiomatic and efficient way to write Scala code. It covers crucial modern practices, such as utilizing functional transforms over traditional loops, embracing pattern matching, using Option/Either for robust error handling instead of null checks or exceptions, and managing concurrency safely. Essential reading for any Scala developer aiming for high-quality, maintainable, and performant codebases.

This skill generates a comprehensive RACI (Responsible, Accountable, Consulted, Informed) matrix for complex projects, product launches, or ongoing business processes. It clarifies ownership, defines decision rights, and maps roles across cross-functional teams (R, A, C, I), ensuring accountability and preventing bottlenecks. Ideal for governance documentation or onboarding new teams.

An adversarial Quality Assurance (QA) pass designed to deep-dive into any codebase for logic errors, security flaws, and functional bugs. Instead of confirming that code 'looks right,' this skill actively attempts to break the code by simulating hostile inputs, tracing critical data paths, and checking for subtle, real-world correctness issues. Essential for high-stakes, critical code reviews.

A comprehensive guide for digital forensics professionals to analyze raw email headers. It details techniques for tracing the true origin of suspicious emails, verifying sender authenticity, and detecting spoofing attacks. Users learn to systematically validate critical security protocols like SPF, DKIM, and DMARC, which is essential for incident response and cybersecurity investigations.

This skill analyzes ransomware cryptocurrency payment flows by utilizing major blockchain intelligence APIs (like Chainalysis and WalletExplorer). It identifies wallet clusters, tracks movements through obfuscation services (mixers, tumblers), and determines fund flows to exchanges, supporting forensic investigations and law enforcement attribution efforts.

A comprehensive guide detailing the systematic workflow for analyzing malicious Linux ELF binaries. It covers essential techniques including static analysis (using readelf, elftools), dynamic tracing (strace, ltrace), and deep reverse engineering (GDB) of various threats like botnets, cryptominers, and ransomware targeting Linux environments, containers, and cloud infrastructure.

This skill performs a deep comparison of two code versions to verify semantic equivalence, going beyond simple syntax diffing. It uses semi-formal tracing techniques to trace both versions against shared specifications and boundary conditions (e.g., null, zero, max/min). Ideal for confirming if a refactor, rewrite, or migration has unintentionally altered the code's behavior, answering the question: "Did I break anything?"

This sophisticated skill is designed to locate the root cause of a confirmed software failure. It performs a systematic, semi-formal tracing process: first tracing backward from the observed failure point (using provided stack traces, assertions, or error messages) to identify the original premise, and then tracing forward to confirm the symptom. It outputs a highly structured report detailing the divergence, premises, and remedy.

This skill is designed to identify subtle and complex logic bugs within a single code file or function. It employs a semi-formal execution tracing methodology, systematically breaking down the suspected bug into five stages: Premises (expected state), Trace (execution path), Divergence (actual deviation), Trigger (reproduction case), and Remedy (fix). It is ideal for scenarios where users suspect code is wrong but cannot specify a concrete failure point.