2,386 件 ・ 関連度順
概要と使いどころ
Implement structured logging with JSON formats, log levels (DEBUG, INFO, WARN, ERROR), contextual logging, PII handling, and centralized logging. Use for logging, observability, log levels, structured logs, or debugging.
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。
Deep code analysis covering security, performance, maintainability, 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。
Essential Git patterns for effective version control, eliminating redundant Git guidance per agent.
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。
TanStack Query (React Query) v5 best practices for data fetching, caching, mutations, and server state management. Use when building data-driven React applications, setting up query configurations, implementing mutations/optimistic updates, configuring caching strategies, integrating with SSR, or fixing v4→v5 migration errors.
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。
Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against 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。
Turborepo monorepo build system guidance. Triggers on: turbo.json, task pipelines, dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. Use when user: configures tasks/workflows/pipelines, creates packages, sets up monorepo, shares code between apps, runs changed/affected packages, debugs cache, or has apps/packages directories.
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。
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
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。
TanStack Pacer best practices for execution control in React — debouncing, throttling, rate limiting, queuing, and batching. Use when implementing search inputs, scroll handlers, API rate limits, task queues, bulk operations, or any scenario requiring controlled execution timing with reactive state.
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。
10 Beste KI-Agenten für die Automatisierung von ... - Unite.AI — 17. Juli 2026 · Ein KI-Agent ist ei
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 Agent Index Categories Find Agent + Submit Compare Alternatives Stacks Advertise API Home / AI Coding Agents Best AI Coding Agents (2026): IDEs, Te
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LoRA · Hugging Face — We propose Low-Rank Adaptation, or LoRA, which freezes the pre-trained model weights and injects trainable rank decomposition …;
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。
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
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。
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
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 and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architectural choices, or establishing decision processes.
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 production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
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。
Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against 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。
Build or review production-ready Tavily SDK and API integrations for web search, extraction, crawling, mapping, and research. Use when implementing Tavily in an agent, RAG pipeline, or application rather than only running one CLI command.
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。
Comprehensive web quality audit covering performance, accessibility, SEO, and best practices. Use when asked to "audit my site", "review web quality", "run lighthouse audit", "check page quality", or "optimize my website".
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。
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
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。
Java Javadoc best practices. Use when adding or reviewing documentation for Java types, methods, packages, and public APIs.
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。
Map tasks to specialist agents. Use when choosing which agent for a job, comparing agent capabilities, or routing to React/Next.js/Playwright/docs/code-quality experts. Keywords: which agent, best agent for this, delegate to expert, agent capability mapping.
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。
Simplifies and refines code for clarity, consistency, and maintainability while preserving all functionality. Use when asked to "simplify code", "clean up code", "refactor for clarity", "improve readability", or review recently modified code for elegance. Focuses on project-specific 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。
You are a documentation expert specializing in creating comprehensive, maintainable documentation from code. Generate API docs, architecture diagrams, user guides, and technical references using AI-powered analysis and industry 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。
You are a documentation expert specializing in creating comprehensive, maintainable documentation from code. Generate API docs, architecture diagrams, user guides, and technical references using AI-powered analysis and industry 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。