3,602 件 ・ 関連度順
概要と使いどころ
Create architecture solution design decisions for AI agent consistency. Use when the user says "lets create architecture" or "create technical architecture" or "create a solution 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。
有馬記念分析システムのアーキテクチャ/レイヤー境界レビュー。docs/ARCHITECTURE.md のレイヤー構成（commands / domain / repositories / models / features / constants / database / utils / types）に対し、レイヤーディレクトリの意味と配置、参照系(queries)と更新系(aggregates)の分離、DB 接続の注入可能性とテスト容易性、リッチドメインモデルの維持（commands 肥大・ドメイン貧血症）、重み・閾値の constants 単一定義、ファイル配置と命名語彙の一致、不要な抽象化、種別分岐のポリモーフィズム化、生成引数の凝集（5個以上は分割シグナル）を検証。純粋性・依存方向の逆流・DB 接続の生成箇所は lint が error で担保するため扱わない。Use when user says 'アーキテクチャレビュー', 'レイヤー境界チェック', 'review architecture', or '依存方向の確認'.
Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
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。
Create professional, dark-themed architecture diagrams as standalone HTML files with SVG graphics. Use when the user asks for system architecture diagrams, infrastructure diagrams, cloud architecture visualizations, security diagrams, network topology diagrams, or any technical diagram showing system components and their relationships.
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。
Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
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。
Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
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。
Systematically evaluate architecture decisions, document trade-offs, and select appropriate patterns. This skill should be used when the user asks about 'architecture decision', 'ADR', 'design pattern selection', 'technology choice', or needs to evaluate architectural trade-offs. Keywords: architecture, ADR, patterns, trade-offs, technical debt, quality attributes, decision record.
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 database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures. Masters SQL/NoSQL/TimeSeries database selection, normalization strategies, migration planning, and performance-first design. Handles both greenfield architectures and re-architecture of existing systems. Use PROACTIVELY for database architecture, technology selection, or data modeling decisions.
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。
実在するファイルや行番号を参照した段階的なコード案内をCodeTour形式で作成し、新任者の学習、設計の理解、PRレビュー、障害原因の調査に役立てるスキル。
システムの構成やデータの流れを、クリックして詳しく読める立体的なHTMLマップに整理します。同じデータから説明文も生成し、設計上の判断や未解決の質問を管理します。
For product and technical management work: turn PRDs, roadmaps, RFCs, architecture reviews, and retros into decision documents. Built around the core query "pm-feature-business-case-deck", with product strategy lead judgment, buyer-ready proof, and this outcome: approve the feature, architecture, roadmap, or incident follow-up.
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。
Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.
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。
Agent skill for architecture - invoke with $agent-architecture
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。
Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.
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 or rewrite architecture subsystem docs, ADRs, and reference material for the engineering team. Use when creating, updating, or reviewing docs under docs/architecture docs/, or when the user asks you to write documentation that describes the system's 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。
Review repository architecture using Ontoly Software Graph and MCP capabilities. Use when asked to explain architecture, module boundaries, package topology, service ownership, or architectural risk.
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。
Authors a Dynamics 365 Finance and Supply Chain Management Solution Blueprint from scratch through a structured, section-by-section architect interview, establishing scope, target operating model, application and data architecture, integration landscape, migration strategy, security model, ALM, testing, deployment, and support approach, with a decision log capturing rationale and rejected alternatives. Use when the user wants to create D365 implementation architecture documentation, start a D365 implementation, design the architecture, prepare a Solution Blueprint, or identify the architectural decisions the programme must make. Do not use for critique of an existing design; that is a review task rather than blueprint authoring.
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 AI agent architectures through requirements discovery, or audit and diagnose architectural flaws in existing agents. Architecture only; excludes implementation and general code review.
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 Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep. When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services
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。
Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Includes tech debt analyzer, team scaling calculator, engineering metrics frameworks, technology evaluation tools, and ADR templates. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
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。
RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.
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。
Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.
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 audit, redesign, or plan their website's structure, URL hierarchy, navigation design, or internal linking strategy. Use when the user mentions 'site architecture,' 'URL structure,' 'internal links,' 'site navigation,' 'breadcrumbs,' 'topic clusters,' 'hub pages,' 'orphan pages,' 'silo structure,' 'information architecture,' or 'website reorganization.' Also use when someone has SEO problems and the root cause is structural (not content or schema). NOT for content strategy decisions about what to write (use content-strategy) or for schema markup (use schema-markup).
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。
Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
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。