Skill UI

AddressSanitizer accelerates fuzz testing by instrumenting C/C++ and unsafe Rust code to detect buffer overflows, use-after-free, and related memory corruption bugs at runtime, with configurable ASAN_OPTIONS for verbosity, abort behavior, and leak control.

AFL++ is an advanced fork of AFL that runs multi-core campaigns, supports diverse mutations, and targets large C/C++ codebases with stable tooling via Docker or host builds.

A comprehensive guide derived from C++ Core Guidelines, enforcing modern, safe, and idiomatic practices for C++17, C++20, and C++23. It emphasizes crucial principles like RAII, type safety, immutability, and proper resource ownership using smart pointers. Use this when writing new features, reviewing existing code, or making architectural decisions to ensure code quality and consistency.

A specialist guide for designing, implementing, and optimizing high-performance C++ applications using modern standards (C++20/23). Expertise covers advanced topics like concepts, coroutines, template metaprogramming, and zero-overhead abstractions. Use this when tackling complex memory management, concurrency bottlenecks, or integrating build systems via CMake, ensuring code meets industrial quality standards through rigorous sanitization and profiling.

Guides an agent through C++17/20 testing with CMake, CTest, and GoogleTest/Mock, covering new or flaky tests, CI gates, coverage builds, and sanitizer diagnostics to keep regression safety in place.

LibFuzzer is LLVM’s in-process coverage-guided fuzzer for C/C++ projects compiled with Clang, providing a quick harness-based setup that can later transition to more advanced fuzzers while maintaining reproducible, high-throughput testing.

llama.cpp is a pure C/C++ library designed for efficient LLM inference, optimized to run on resource-constrained environments. It excels in scenarios where high-end NVIDIA GPUs (CUDA) are unavailable, making it ideal for Apple Silicon Macs, AMD/Intel GPUs, or edge deployment devices like Raspberry Pi. It supports GGUF quantization formats, enabling significant memory reduction and speed improvements for local, cross-platform AI applications.

This expert guide provides comprehensive best practices for developing robust, high-performance C++ code within Unreal Engine 5.x. It covers critical topics such as UObject lifecycle management, adhering to Epic Games' strict coding conventions, optimizing performance-critical sections (e.g., avoiding unnecessary Ticking), and correctly using soft references for asset loading. Use this skill for professional game development tasks requiring deep knowledge of the Unreal reflection system and advanced C++ patterns.

Detects missing zeroization of secrets and flags compiler-optimized removals with mandatory assembly/IR evidence, helping auditors verify C/C++/Rust cryptographic code through dataflow, CFG, and runtime validation.

A specialized tool for auditing source code (C/C++/Rust) to ensure sensitive data (keys, passwords, PII) is properly zeroized. It analyzes memory handling at the assembly and IR level to detect if compiler optimizations, such as dead-store elimination, have accidentally removed or weakened the secure cleanup process. Essential for maintaining security in critical codebases.

Learn how to integrate AFL++ (American Fuzzy Lop Plus Plus) into Continuous Integration/Continuous Deployment (CI/CD) pipelines. This guide details the process of using coverage-guided fuzzing to discover critical vulnerabilities, such as memory corruption, input handling flaws, and logic bugs, in compiled C/C++ applications that process untrusted input.

An advanced debugging skill designed for AI agents. It utilizes gdb-cli to provide intelligent assistance for C/C++ programs, enabling the analysis of core dumps, debugging live processes, and investigating complex issues like crashes, deadlocks, and memory corruption. It correlates runtime state inspection with source code context for deeper insights.