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概要と使いどころ
Prompt engineering frameworks for building, testing, versioning, and evaluating prompts: chain-of-thought, few-shot, regression testing, and rubrics. Use when designing production prompts, running A/B tests, or building prompt libraries.
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 the user asks to "build a mobile app", "scaffold React Native project", "create SwiftUI views", "set up Jetpack Compose", "optimize mobile performance", "configure Expo Router navigation", "implement offline-first storage", "submit to App Store", or "profile mobile rendering". Expert mobile development covering iOS (Swift/SwiftUI), Android (Kotlin/Compose), React Native, and Flutter for native and cross-platform applications.
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。
Manage parallel development with Git worktrees: creation with port allocation, environment sync, branch isolation, and cleanup. Use when working multiple branches at once, running parallel CI validations, or isolating agent 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。
Design observability strategies: SLI/SLO frameworks, alerting, and dashboards. Use when instrumenting a production service, tuning alert rules, designing Grafana dashboards, defining SLOs and error budgets, or reducing alert fatigue.
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。
Performance profiling for Node.js, Python, and Go: CPU flamegraphs, memory leak detection, bundle analysis, query optimization, and k6 load testing. Use when diagnosing slow endpoints, memory growth, large bundles, or traffic spikes.
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。
End-to-end testing with Playwright: test generation, page objects, locator strategy, flaky- test diagnosis, visual regression, and CI integration. Use when writing E2E tests, fixing flaky tests, or migrating from Cypress/Selenium.
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 "analyze Helm charts", "validate Helm values", "review chart structure", "check Kubernetes Helm templates", or "audit chart dependencies and configuration".
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。
Environment and secrets management lifecycle: .env scaffolding, validation, leak detection, and rotation across Vault, AWS SSM, 1Password, and Doppler. Use when setting up projects, scanning for leaked secrets, or rotating credentials.
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。
Systematic PR review with blast-radius analysis, security scanning, and breaking-change and test-coverage deltas. Use when reviewing PRs that touch shared libraries, APIs, database schemas, auth, or security-sensitive code.
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。
Design RAG pipelines: chunking, retrieval evaluation, and architecture. Use when building a RAG system, selecting a chunking strategy, choosing a vector database, optimizing retrieval quality, or evaluating with RAGAS metrics.
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 "plan a red team engagement", "scope a penetration test", "design a security assessment methodology", "create rules of engagement", or "plan an adversary simulation".
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。
Validate and score Claude Code skill packages for quality, completeness, and best-practice compliance. Tests Python scripts, checks YAML frontmatter, and generates reports. Use when creating, validating, or auditing skill packages.
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。
Automates release management with changelog generation, semantic versioning, and release readiness checks. Use when preparing releases, generating changelogs, bumping versions, or validating release candidates.
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。
Orchestrate end-to-end release pipelines. Use when running pre-release validation, generating changelogs, bumping semantic versions, scoring deployment readiness, or gating releases with secret scanning and GO/NO-GO checks.
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。
Microsoft 365 tenant administration for Global Administrators. Use for tenant setup, Azure AD user management, Exchange Online and Teams config, Conditional Access policies, license management, and PowerShell bulk-operation scripts.
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。
Design, review, and validate Google Cloud (GCP) architectures. Use when choosing GCP compute, storage, networking, or identity services, or applying the Google Cloud Architecture Framework (reliability, security, cost, performance).
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 (Model Context Protocol) servers with tool definitions, resource providers, prompt templates, and transports. Use when exposing APIs to AI agents, building tool servers, converting OpenAPI to MCP, or creating MCP integrations.
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 operational runbooks from codebase analysis covering deployment, incident response, scaling, and monitoring, with copy-paste commands and rollback steps. Use when bootstrapping ops docs, preparing for on-call, or post-incident.
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。
Feature flag strategy, lifecycle, and operations. Use when designing a flag taxonomy, planning a gradual rollout, building kill switches, auditing flag debt, defining governance, running progressive delivery, or rolling back via flags.
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。
Manage and optimize monorepos with Turborepo, Nx, pnpm workspaces, and Changesets. Use when working in monorepos, running impact analysis, optimizing build times with remote caching, migrating from multi-repo, or coordinating publishing.
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 "estimate LLM costs", "count tokens in prompts", "optimize prompt token usage", "compare model pricing", or "reduce LLM API costs".
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 SaaS boilerplate with auth, database schemas, Stripe billing, multi-tenancy, API routes, and dashboard UI on a Next.js/TypeScript/Tailwind stack. Use when starting a new SaaS product, subscription app, or multi-tenant platform.
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。
Testing for React/Next.js with Jest, React Testing Library, and Playwright. Use when generating tests, writing unit tests, analyzing coverage, scaffolding E2E tests, configuring Jest, or improving test quality.
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。
Prompt engineering and LLM evaluation. Use when optimizing prompts, designing prompt templates, evaluating LLM outputs, building agentic systems, implementing RAG, creating few- shot examples, or designing structured-output workflows.
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。