4,256 件 ・ 関連度順
概要と使いどころ
You are a code education expert specializing in explaining complex code through clear narratives, visual diagrams, and step-by-step breakdowns. Transform difficult concepts into understandable explanations for developers at all levels.
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。
Guide for VS Code extension development from scaffolding to Marketplace publication
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。
Creates devcontainers with Claude Code, language-specific tooling (Python/Node/Rust/Go), and persistent volumes. Use when adding devcontainer support to a project, setting up isolated development environments, or configuring sandboxed Claude Code workspaces.
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。
Generate comprehensive, developer-friendly API documentation from code, including endpoints, parameters, examples, and best practices
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。
API documentation workflow for generating OpenAPI specs, creating developer guides, and maintaining comprehensive API documentation.
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。
Guide for using MSBuild Server to improve CLI build performance. Only activate in MSBuild/.NET build context. Activate when developers report slow incremental builds from the command line, or when CLI builds are noticeably slower than IDE builds. Covers MSBUILDUSESERVER=1 environment variable for persistent server-based caching. Do not activate for IDE-based builds (Visual Studio already uses a long-lived process).
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。
Guide developers through capturing diagnostic artifacts to diagnose production .NET performance issues. Use when the user needs help choosing diagnostic tools, collecting performance data, or understanding tool trade-offs across different environments (Windows/Linux, .NET Framework/modern .NET, container/non-container).
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。
Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design.
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。
Guide for interpreting ResolveProjectReferences time in MSBuild performance summaries. Only activate in MSBuild/.NET build context. Activate when ResolveProjectReferences appears as the most expensive target and developers are trying to optimize it directly. Explains that the reported time includes wait time for dependent project builds and is misleading. Guides users to focus on task self-time instead. Do not activate for general build performance -- use build-perf-diagnostics instead.
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。
Serverless and microservices development guidelines covering FastAPI, cloud-native patterns, API gateways, and best practices for scalable serverless architectures.
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。
Estimate AI-assisted and hybrid human+agent development work with research-backed PERT statistics and calibration feedback loops
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。
PyTorch deep learning development with transformers, diffusion models, and GPU 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。
You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur
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。
Machine learning development with JAX, functional programming patterns, and high-performance computing.
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。
Large Language Model development, training, fine-tuning, and deployment best practices.
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。
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
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。
Best practices for scikit-learn machine learning, model development, evaluation, and deployment in Python
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。
Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.
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。
Expert guidance for deep learning, transformers, diffusion models, and LLM development with PyTorch, Transformers, Diffusers, and Gradio.
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。
Guidelines for deep learning development with PyTorch, Transformers, Diffusers, and Gradio for LLM and diffusion model work.
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。
You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.
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。
Improve AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.
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。
Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.
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。
LLMs, prompt engineering, RAG systems, LangChain, and AI application development
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。