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概要と使いどころ
Provides architectural pattern knowledge for designing feature implementations including MVC, event-driven, microservices, and CQRS patterns. Use when designing system architecture or choosing implementation patterns.
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SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
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Decision matrix for selecting multi-agent topologies (Supervisor, Swarm, Hierarchical, Conductor) with token economics, failure modes, and escalation paths
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Generates architecture, database, and system diagrams using Mermaid syntax. Creates visual representations of system architecture, database schemas, component relationships, data flows, and standalone HTML exports.
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N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
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Architecture review and design validation. Evaluates system designs against best practices, identifies anti-patterns, and ensures architectural decisions align with non-functional requirements.
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 Android development expert covering Jetpack Compose, Kotlin coroutines/Flow, Architecture Components, Hilt DI, Navigation, testing, performance, Material Design 3, and modern Android patterns (MVI, Clean Architecture).
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Phase 2 of 5 — collaborative system design plus change-footprint mapping; outputs an ARCH doc for generate-tasks. Use only when the user asks to run Phase 2, plan the architecture, or design the solution — never trigger automatically from a design question.
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AWS の構成図を draw.io の XML（.drawio）で描く。公式の AWS4 アイコンを使い、タイトルや凡例や番号バッジのような装飾を足さず、どのサービスがどこにあって何とつながっているかだけで読める図にする。AWS 構成図、アーキテクチャ図、インフラ構成図、ネットワーク構成図、VPC の図を描いてほしいとき、draw.io で AWS の図を作りたいとき、既存の構成図を直したいときは必ずこの Skill を使う。Use this whenever the user asks for an AWS architecture diagram, cloud infrastructure diagram, VPC diagram, or a draw.io file of AWS resources, even if they don't say "draw.io". Mermaid、PlantUML、Python の diagrams ライブラリなど、ほかの形式を指定されたときは使わない。Do not use it when the user explicitly asks for Mermaid, PlantUML, or the Python diagrams library.
Convert a semantic core into crawlable SEO and LLM-friendly information architecture. Use this skill when the user asks for URL structure, page taxonomy, canonical rules, hreflang groups, page roles, pillar/topic/news/article/blog/project separation, multilingual route strategy, or a durable content model such as one short brief plus one longform article. It prevents duplicate public content bodies and hands link-graph work to internal-link-graph-architect.
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Build evidence-labeled semantic cores for SEO, LLM-readable architecture, and site information design. Use this skill when the user asks for semantic core, query clusters, search intents, audience segments, entity/topic maps, language or locale priorities, competitor/source evidence, pillar-topic planning, or a structured handoff before URL architecture and internal linking. It must mark unknown search volume, difficulty, and ranking data as unknown instead of inventing metrics.
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Generates a structured Project Brief — a comprehensive markdown document that extracts goals, architecture, knowledge file inventory, Custom Instructions summary, Memory contents, current state, ecosystem position, and key decisions from a Claude Project. Briefs serve as uploadable context documents: add one to any other Project for immediate deep awareness of the source Project's purpose, architecture, and progress. Use when user says "create a brief," "brief this project," "extract project context," "generate a project summary for another project," "I need to share this project's context," "prepare this project for cross-project reference," or "document this project." Also use when the user is preparing to work across Projects and needs portable context. Do NOT use for session handoffs, project audits, or Memory optimization (use rootnode-session-handoff, rootnode-project-audit, or rootnode-memory-optimization respectively, if available).
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。
Specialized software engineering prompt methodology for Claude. Use when building prompts for system design, code review, incident response, security analysis, API design, architecture decisions, RFCs, ADRs, runbooks, or technical leadership. Trigger on: "build a prompt for code review," "system design prompt," "SRE prompt," "security review prompt," "incident response prompt," "API design prompt," "architecture decision prompt," "RFC prompt," "runbook prompt." Provides 11 tested approaches across identity, reasoning, and output for engineering analysis. Do NOT use for general coding help, writing code, or debugging — this builds prompts that shape engineering analysis, not code itself. Do NOT use for evaluating existing prompts (use rootnode-prompt-validation if available).
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コードベースのアーキテクチャを 6 つの専門エージェントチーム（Claude 5体 + Codex 1体）で 多角的に分析し、リスク・デグレしやすい箇所・改善ポイントを洗い出すスキル。 パフォーマンス、スケーラビリティ、信頼性、セキュリティ、運用、DX、データ整合性、依存関係の 8 観点を 5 グループに分担し、さらに Codex がクロスカットレビュアーとして横断分析する。 エージェント同士が反論・補足・自由な議論を行い、合意形成した結果をレポートとして出力する。 どのプロジェクトでも使える汎用スキル。 Use when: アーキテクチャを分析したい、リファクタリング前にリスクを把握したい、 デグレしやすい箇所を知りたい、コードの健全性を確認したい、大きめの実装前に注意点を洗い出したい、 技術的負債を可視化したい、コードベースの品質を監査したい。 Triggers: "arch review", "アーキテクチャ分析", "アーキテクチャレビュー", "リスク分析", "コード監査", "codebase audit", "技術的負債", "デグレしやすい", "architecture analysis", "risk analysis", "コードの健全性", "品質チェック", "実装前の確認"
Use when the user is deciding, reviewing, or second-guessing a software architecture or tech-stack choice — monolith vs microservices vs serverless vs event-driven, backend language, database type, caching, CQRS/event sourcing, polyglot, or a migration like Strangler Fig. Triggers on "should I use microservices", "which database", "tech stack for", "system design", or "architecture review". For how to deploy, operate, and scale that design (CI/CD, cloud, Kubernetes, IaC), use devops.
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Use when the user needs to deploy, operate, secure, or scale running infrastructure — cloud architecture (multi-region, VPC, FinOps), CI/CD and deployment strategies, secrets/IAM/supply-chain security, observability and SLO alerting, SRE and incident response, Kubernetes vs ECS and autoscaling, Terraform/Pulumi/CDK, or platform engineering and DORA metrics. Also for generating runbooks, pipeline configs, Terraform modules, or Kubernetes manifests. For choosing the system's architecture or stack before it runs (monolith vs microservices, which database), use software-architect.
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。
Multi-phase deep codebase review with severity ratings and structured output. Covers architecture, security, code quality, and UX/accessibility in a single coordinated pass. Produces a prioritized findings table suitable for direct conversion to GitHub issues via the create-github-issues skill.
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Separate expensive observation from cheap decision-making in autonomous agent loops using a two-clock architecture. A fast clock accumulates data into a digest file; a slow clock reads the digest and acts only when something is pending. Idle cycles cost nothing because the action clock returns immediately after reading an empty digest. Use when building autonomous agents that must observe continuously but can only afford to act occasionally, when API or LLM costs dominate and most cycles have nothing to do, when designing cron-based agent architectures with observation and action phases, or when an existing heartbeat loop is too expensive because it calls the LLM on every tick.
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Build a plugin or adapter for a CLI tool using the abstract base class pattern. Covers defining the contract (static fields, required methods), choosing an installation strategy (symlink, copy, append-to-file), implementing detection, install/uninstall with idempotency, listing, auditing, and registering the plugin. Use when adding support for a new framework to a CLI installer, building a plugin system for any multi-target tool, or extending an existing adapter architecture.
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Migrate workloads from Google Cloud Platform to AWS — including AI and agentic workloads regardless of cloud provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, Google Cloud migration, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency/quality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.
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MUST USE when designing ClickHouse architectures, selecting between ingestion or modeling patterns, or translating best practices into workload-specific system designs. Complements clickhouse-best-practices with decision frameworks and explicit provenance labels.
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Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations. Use when asked to "review the architecture", "engineering review", or "lock in the plan".
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When making code changes or reviewing existing code, check if architecture diagram matches implementation, and keep the diagram in sync.
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Slice a NowStack Mobile app's .agents/plan/PRD.md + .agents/plan/ARCHITECTURE.md into well-scoped, implementable task files under .agents/plan/tasks/, each an autonomous 1–3h vertical slice (Convex schema/function → Expo screen → wiring) with success criteria, dependencies, and verification commands. Use for "create tasks", "ns tasks", "break this into tickets", or as the third planning step after ns-prd and ns-architecture. Both docs must exist first.
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。