205 件 ・ 関連度順
概要と使いどころ
Guides C++ code toward modern idioms (C++20/23/26). Use when writing new C++ code, modernizing legacy patterns, or working on security-critical C++. Replaces raw pointers with smart pointers, SFINAE with concepts, printf with std::print, error codes with std::expected.
日本語の概要は準備中です。原文の説明を表示しています。
Provides file paths to language-specific extension files for the code-testing pipeline. Read this reference-only catalog for extension guidance files (e.g., dotnet.md for .NET, cpp.md for C++). Agents and skills read its bundled files directly; do not invoke this catalog through the model's skill tool.
日本語の概要は準備中です。原文の説明を表示しています。
Enable or disable MCP tools by name in batch. Persists the change via `UnityMcpPluginEditor.Instance.Save()` only when at least one tool actually flipped. Returns per-input success flags plus optional operation logs.
日本語の概要は準備中です。原文の説明を表示しています。
Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp, and Ollama with structured JSON output.
日本語の概要は準備中です。原文の説明を表示しています。
Pick the serving stack and per-runtime memory flags (vLLM, SGLang, llama.cpp, TensorRT Edge-LLM) for an LLM/VLM workload on any NVIDIA Jetson.
日本語の概要は準備中です。原文の説明を表示しています。
Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions.
日本語の概要は準備中です。原文の説明を表示しています。
[omh] Self-hosted LLM serving on GPUs: choose the serving engine and quantization from decision tables, prepare deployment as an idempotent runbook with observed-only verification, and measure the endpoint with the standard TTFT/TPOT/goodput protocol. Use when the user says: inference-serving, inference serving, serve this model, serve the model, model serving, serving endpoint, vllm, llama.cpp.
日本語の概要は準備中です。原文の説明を表示しています。
Build MCP servers for Copilot Chat using the OpenAI Apps SDK or MCP Apps SDK widget rendering support (any language). Use this skill when: - Creating MCP servers that integrate with M365 Copilot declarative agents - Building rich interactive widgets (React + Fluent UI) that render in Copilot Chat - Implementing tools that return structuredContent for widget rendering - Adapting an existing MCP server to support Copilot widget rendering - Setting up devtunnels for localhost MCP server exposure - Configuring mcpPlugin.json manifests with RemoteMCPServer runtime Do NOT use this skill for general agent development (scaffolding, manifests, deployment) — use declarative-agent-developer instead. This skill is ONLY for MCP server + widget development. Triggers: "MCP server for Copilot", "OpenAI Apps SDK", "Copilot widget", "structuredContent", "MCP plugin", "devtunnels MCP", "OAI app", "widget rendering", "UI widget"
日本語の概要は準備中です。原文の説明を表示しています。
Delegate a coding task to Aider (`aider`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Aider - phrasings like "have Aider do X", "delegate this to aider", "run it through Aider", or "use Aider to implement/fix/refactor" - or wants to run a queue of coding tasks through Aider while staying the reviewer. This includes asking Aider to drive a local or self-hosted OpenAI-compatible endpoint ("have Aider use my local model", "run Aider against llama.cpp / Ollama / vLLM / LM Studio"), which Aider reaches via `--api-base`. DO NOT USE for local-model or coding requests that do not name Aider, for tasks small enough to do inline, or when the user wants the code written directly without delegating.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to A/B test App Store product page elements to improve conversion rate. Also use when the user mentions "A/B test", "product page optimization", "test my screenshots", "test my icon", "conversion rate optimization", "CPP", or "custom product pages". For screenshot design, see screenshot-optimization. For metadata optimization, see metadata-optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Uninstall or hard-clean OpenClaw Companion, Windows node, native Gateway/MXC, WSL Gateway, and managed llama.cpp/Local AI state for a clean retest. Choose the existing dev CLI uninstall or the reviewed hard-clean procedure, inventory exact targets, and obtain destructive confirmation before acting.
日本語の概要は準備中です。原文の説明を表示しています。
仅在创建/更新/修复 C++ 测试、配置 GoogleTest/CTest、诊断失败或不稳定的测试、以及添加覆盖率或消毒器时使用。
日本語の概要は準備中です。原文の説明を表示しています。
仅用于编写/更新/修复C++测试、配置GoogleTest/CTest、诊断失败或不稳定的测试，或添加覆盖率/消毒器时使用。
日本語の概要は準備中です。原文の説明を表示しています。
仅在编写/更新/修复 C++ 测试、配置 GoogleTest/CTest、诊断失败或不稳定的测试、或添加覆盖率/检测器（Sanitizers）时使用。
日本語の概要は準備中です。原文の説明を表示しています。
Write idiomatic C++ code with modern features, RAII, smart pointers, and STL algorithms. Handles templates, move semantics, and performance optimization. Use PROACTIVELY for C++ refactoring, memory safety, or complex C++ patterns.
日本語の概要は準備中です。原文の説明を表示しています。
Write Unreal Engine 5 C++ gameplay code: the UCLASS/UPROPERTY/UFUNCTION reflection macros, the Gameplay Framework (GameMode, Pawn, Character, PlayerController, Actor components), and the module Build.cs. Use when writing or debugging UE C++, deriving from AActor/ACharacter/ AGameModeBase, exposing properties to the editor or Blueprints, or when the user mentions Unreal C++, UCLASS, GENERATED_BODY, GameMode, ACharacter, or .Build.cs.
日本語の概要は準備中です。原文の説明を表示しています。
Use only when writing/updating/fixing C++ tests, configuring GoogleTest/CTest, diagnosing failing or flaky tests, or adding coverage/sanitizers.
日本語の概要は準備中です。原文の説明を表示しています。
Build private, on-device AI features on iPhone, iPad, and Mac with Foundation Models, Core ML, MLX Swift, or llama.cpp. Use when choosing an Apple-local model runtime, building an Apple Intelligence chatbot or tool-calling feature, running an LLM on Apple Silicon, converting or compressing a Python model for Core ML, or comparing on-device inference backends. For Swift Core ML loading and prediction code, use the coreml skill.
日本語の概要は準備中です。原文の説明を表示しています。
C++ naming, formatting, static analysis, and RTTI rules for LuisaCompute.
日本語の概要は準備中です。原文の説明を表示しています。
Use when a Unity 6.3 game is slow or stutters: low fps, frame spikes, hitches when entering areas or on first effects, GC spikes, too many draw calls or SetPass calls, CPU vs GPU bound questions, Profiler, Profile Analyzer, Memory Profiler, Frame Debugger or Project Auditor work, GPU Resident Drawer or SRP Batcher setup, LOD and Mesh LOD, shader warm-up and variants, memory or VRAM budgets, IL2CPP and build size, or proving a fix with numbers from a player.
日本語の概要は準備中です。原文の説明を表示しています。
California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) compliance advisor — business threshold analysis, consumer rights fulfillment (access, delete, correct, opt-out of sale/sharing, limit SPI, ADMT opt-out), privacy notice drafting, service provider vs. contractor vs. third-party classification, sensitive personal information (SPI) handling, data minimization, opt-out mechanisms (including GPC), cybersecurity audits and risk assessments (live since Jan 1, 2026), ADMT obligations (effective 2026, deadline Jan 1, 2027), CPPA enforcement (Disney $2.75M, PlayOn $1.1M, Ford $375K), penalty exposure, GDPR comparison, and gap assessments for businesses operating in or targeting California residents.
日本語の概要は準備中です。原文の説明を表示しています。
Writes, optimizes, and debugs C++ applications using modern C++20/23 features, template metaprogramming, and high-performance systems techniques.
日本語の概要は準備中です。原文の説明を表示しています。
California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) compliance advisor — business threshold analysis, consumer rights fulfillment (access, delete, correct, opt-out of sale/sharing, limit SPI, ADMT opt-out), privacy notice drafting, service provider vs. contractor vs. third-party classification, sensitive personal information (SPI) handling, data minimization, opt-out mechanisms (including GPC), cybersecurity audits and risk assessments (live since Jan 1, 2026), ADMT obligations (effective 2026, deadline Jan 1, 2027), CPPA enforcement (Disney $2.75M, PlayOn $1.1M, Ford $375K), penalty exposure, GDPR comparison, and gap assessments for businesses operating in or targeting California residents.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building native extensions for Godot — godot-cpp (C++) or gdext (Rust), binding classes, building, and GDScript/C# interop
日本語の概要は準備中です。原文の説明を表示しています。