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C++ coding standards based on the C++ Core Guidelines (isocpp.github.io). Use when writing, reviewing, or refactoring C++ code to enforce modern, safe, and idiomatic practices.
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Upgrade C, C++, and Fortran MEX source files from the Separate Complex (SC) API to the Interleaved Complex (IC) API. Use when converting mxGetPr/mxGetPi to mxGetComplexDoubles, migrating MEX files to -R2018a, adding MX_HAS_INTERLEAVED_COMPLEX guards for SC/IC guarded builds, or modernizing legacy MEX code that uses mxGetData/mxSetData/mxGetImagData/mxSetImagData. Covers C (.c), C++ (.cpp, .cxx), and Fortran (.F, .f90) MEX functions. Triggers on: interleaved complex, IC MEX, mex upgrade, mex migration, separate complex, mxGetPi, mxGetPr replacement, -R2018a, complex MEX, Fortran MEX, .F MEX file, C++ MEX, .cpp MEX file, MEX performance, MEX slow complex, MEX call overhead, improve MEX performance complex.
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C++ coding standards based on the C++ Core Guidelines (isocpp.github.io). Use when writing, reviewing, or refactoring C++ code to enforce modern, safe, and idiomatic practices.
中文简介正在准备中。当前显示原文说明。
游戏安全逆向专项。当任务涉及游戏反作弊分析、Unity/UE 逆向、内存扫描、DBI 框架、IL2CPP 分析、 游戏保护壳（VMProtect/Themida）脱壳、Cheat Engine、游戏 Mod 开发时使用本 skill。 触发关键词：游戏逆向、反作弊、Cheat Engine、Unity、IL2CPP、Unreal Engine、x64dbg、游戏安全、 game hacking、anti-cheat、EAC、BattlEye、Vanguard。
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Use when imp outputs differ between two paths that should agree - chunk sizes, prefill vs decode, prefix-cache resend, two engines (imp vs llama.cpp vs HF), two builds or kernels - "output changes with chunk size", "first token differs", "logprobs moved", "which layer diverges", "who is right, imp or llama.cpp", "near-tie". Do NOT use for repetition loops or garbage output (check-degeneration), a new arch that loads wrong (add-model-arch), or perf (benchmark-cuda).
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Use when a C++ template error needs decoding, a template needs a concept or requires-clause instead of SFINAE, or template instantiation is slowing compilation. Not for C++20 modules: use cpp-modules.
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Run a GGUF model locally with llama.cpp, and find one on the HF Hub.
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Use when pulling or downloading a new llamacpp model. The active ROCm image (kyuz0/amd-strix-halo-toolboxes) fails to start in the ephemeral pull container without ROCm device access. Must temporarily switch to the standard CPU image.
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Review Yuzu C++ source changes for C++23 correctness, idiomatic standard-library use, ABI boundaries, threading primitives, and cross-compiler portability across GCC, Clang, MSVC, and Apple Clang. Use for any governance Gate 3 review when `.cpp`, `.hpp`, or `.h` files change.
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Review Yuzu C++ source changes for resource ownership, RAII, borrowed lifetimes, C ABI contexts, casts, process/syscall boundaries, callbacks, threads, and sanitizer coverage. Use for any governance Gate 3 review when C++ files change, paired with cpp-expert.
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C++ coding standards based on the C++ Core Guidelines (isocpp.github.io). Use when writing, reviewing, or refactoring C++ code to enforce modern, safe, and idiomatic practices.
中文简介正在准备中。当前显示原文说明。
llama.cpp local GGUF inference + HF Hub model discovery.
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Executa inferência de LLM em CPU, Apple Silicon e GPUs consumer sem hardware NVIDIA. Use para edge deployment, Macs M1/M2/M3, GPUs AMD/Intel ou quando CUDA não está disponível. Suporta quantização GGUF (1,5-8 bits) para redução de memória e aceleração de 4-10× vs PyTorch em CPU.
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Formato GGUF e quantização llama.cpp para inferência eficiente em CPU/GPU. Use ao implantar modelos em hardware de consumidor, Apple Silicon, ou quando precisar de quantização flexível de 2-8 bits sem requisitos de GPU.
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Apply the local C++ coding conventions of the EMULATORS framework. Use when Codex adds, edits, reviews, or scaffolds C++ code in this repository, especially new classes, headers, cpp files, CORE/COMMODORE module code, emulator components, registers, chips, memory, sound, IO, commands, or InfoClass-derived objects.
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Write openFrameworks prototypes into the lab — real C++ (ofApp.h, ofApp.cpp, main.cpp) that builds into an app with the projectGenerator and make. Use for native/desktop sketches, performance-sensitive work, OpenGL, audio input, sensors, anything that has to be an application rather than a page.
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llama.cpp local GGUF inference + HF Hub model discovery.
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Expert en développement C++ (modern C++20, STL, memory management, game engines, embedded)
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When the user wants to set up, optimize, or scale Apple Search Ads (ASA) campaigns — including keyword bidding, match types, campaign structure, Creative Product Sets, CPP routing, and ROAS optimization. Use when the user mentions "Apple Search Ads", "ASA", "Search Ads", "Search tab ads", "Today tab ads", "CPT", "TTR", "Search Match", "exact match", "broad match", "CPP in ads", "ASA bidding", or "Search Ads budget". For Meta/Google UAC/TikTok paid UA, see ua-campaign.
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GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
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Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.
中文简介正在准备中。当前显示原文说明。
C++ coding standards based on the C++ Core Guidelines (isocpp.github.io). Use when writing, reviewing, or refactoring C++ code to enforce modern, safe, and idiomatic practices.
中文简介正在准备中。当前显示原文说明。
协助编写和修复C++测试，配置GoogleTest与CTest，调查失败或结果不稳定的原因，并测量测试覆盖范围、配置检测内存误用与并发竞争的运行时检查。
使用JSON、正则表达式、Pydantic类型定义或固定选项约束LLM输出，将文字中提取的信息和分类结果整理为便于后续程序使用的格式。