「architect」の検索結果

Architecture-level decisions for putting a CDN in front of a web app's static assets, API responses, and file/media delivery: provider selection (hyperscaler vs. specialist $/GB), signed-URL / tokenized access for gating private content at the edge, cache invalidation strategy (versioned URLs vs. purge APIs), origin shield / tiered caching for high-miss-rate content, and CDN-layer geo-restriction. Use when deciding which CDN to put in front of a new or growing service, when private/paywalled files need edge delivery without an origin round-trip per request, or when purge/invalidation behavior is being designed rather than debugged. NOT for HTTP cache-control header syntax, Vary, stale-while-revalidate, or surrogate-key purge mechanics (see `cdn-cache-control-headers`); NOT for Cloudflare-specific product configuration once Cloudflare is already chosen (see `cloudflare`); NOT for video-specific transcoding, adaptive bitrate ladders, or streaming-protocol packaging (see `managed-video-streaming-pipeline`).

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。

Choose, compare, and decompose work into the right coordination topology: dag, workflow, manager-driven team, swarm, blackboard, team-builder, or recurring loop. Use when the coordination shape is unclear, when you need topology-native breakdown instructions instead of a generic DAG, or when planning topology and runtime topology may differ. NOT for actual execution, node-level skill matching, or framework/tool installation.

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。

Apply Conway's homomorphism principle to multi-agent system design, recognizing that agent coordination structure predetermines system architecture and capability.

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。

Treat tokens as a coding swarm's cost-of-goods-sold and legibility engine while accounting for finite subscription allowance when per-call price is unknown. Covers provider windows, remaining-usage evidence, burn forecasts, preemptive checkpoint/model switching, per-agent budgets, compaction, shared digests, context degradation, and spend metering. Activate on: "token budget", "context budget", "compaction strategy", "briefing as compression", "context rot", "summarization collapse", "COGS for agents", "subscription usage remaining", "five-hour or weekly limit", "burn forecast", "model switch before limit", or "/context-economics-for-agent-swarms". NOT for: memory architecture (use always-on-agent-architecture), single-prompt wording (use prompt-engineer), mechanism-design proofs (use nisan-et-al-2007-algorithmic-game-theory), physical containment (use sandboxed-adversarial-test-harness), or production rebodiment and fencing (use agent-resurrection-and-body-continuity).

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 performant animation systems with Framer Motion, GSAP, View Transitions API, and spring physics. Activate on: page transitions, micro-interactions, scroll animations, layout animations, spring physics. NOT for: CSS-only hover effects (use css-in-js-architect), video/canvas rendering (use creative-coding-expert).

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。

App Store and Google Play submission automator with Fastlane, screenshot automation, metadata management, and TestFlight/internal testing. Activate on: app store submission, Fastlane, TestFlight, Google Play Console, screenshot automation, metadata management, app review, code signing, provisioning profiles. NOT for: CI/CD pipeline setup (use github-actions-pipeline-builder), app architecture (use react-native-architect), analytics (use mobile-analytics-crash-reporting-expert).

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。

How to design contextual inputs for an always-on AI agent with episodic memory. Covers what data to feed the agent, how to structure observations and triggers, ambient context capture (screen, audio, calendar), context window budgeting, and retrieval strategies that keep the agent grounded in what's actually happening. Activate on: "what should the agent observe", "context inputs for agent", "ambient context capture", "agent triggers", "agent input design", "screenpipe integration", "context window budget", "what data to feed my agent", "/always-on-agent-inputs". NOT for: memory architecture and storage (use always-on-agent-architecture), application ideas (use always-on-agent-applications), safety concerns (use always-on-agent-safety).

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。

Android background task specialist for WorkManager, Foreground Services, Doze mode, and battery optimization. Activate on: WorkManager, background task Android, Foreground Service, Doze mode, battery optimization, periodic work, background sync Android, JobScheduler. NOT for: iOS background tasks (use swiftui-data-flow-expert), React Native background (use mobile-offline-sync-architect), UI architecture (use jetpack-compose-navigation-expert).

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。

Safety-case design for always-on agents with episodic memory. Covers data hygiene, privacy and security risk surfaces, cost controls, scope, user dependency concerns, retention, incident containment, and responsible deployment evidence. It identifies hazards and asks for named controls, tests, owners, and residual uncertainty; it does not provide legal, clinical, youth-safety, or jurisdictional determinations. Activate on: "agent safety", "always-on agent privacy", "agent cost control", "persistent agent risks", "AI companion safety", "agent data hygiene", "runaway agent costs", "parasocial AI risk", "/always-on-agent-safety". NOT for: architecture design (use always-on-agent-architecture), input design (use always-on-agent-inputs), application brainstorming (use always-on-agent-applications), healthcare compliance specifically (use hipaa-compliance).

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。

Declare an agentic application's interaction disclosure, state, context, capabilities, and effect-control boundaries. Use for a reviewable design specification and static consistency audit before implementation. NOT for proving that controls are deployed or enforced, exposing private chain-of-thought, selecting a model/router, or designing a multi-agent protocol.

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 bounded applications and workflows for an always-on AI agent with episodic memory. Covers product ideas, persistence-dependent workflows, and constructed examples that make delegation, interruption, evidence, and opt-out explicit. Activate on: "what can an always-on agent do", "persistent agent use cases", "agent applications", "proactive agent ideas", "what to build with episodic memory", "always-on agent product", "personal AI assistant ideas", "/always-on-agent-applications". NOT for: building the architecture (use always-on-agent-architecture), designing inputs (use always-on-agent-inputs), safety and privacy (use always-on-agent-safety).

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。

SERP-based semantic topic clustering for content architecture planning. Groups keywords by actual Google SERP overlap (not text similarity), designs hub-and-spoke content clusters with internal link matrices, and generates interactive visualizations. Optionally executes content creation if claude-blog is installed. Use when user says "topic cluster", "content cluster", "semantic clustering", "pillar page", "hub and spoke", "content architecture", "keyword grouping", or "cluster plan".

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。

Retired pointer for Next.js SSR doctrine. Use when something references nextjs-ssr-architecture; read the ssr-zero-layout-shift skill 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。

This skill should be used when the user asks to "ドキュメントを更新して", "sync the docs", "update CLAUDE.md after this change", "実装に合わせてドキュメントを直して", or notices that docs have drifted from the codebase. Diffs git history to identify what changed, proposes targeted updates to CLAUDE.md, docs/architecture.md, docs/requirements.md, and README.md, then applies only approved changes.

Guide the user through starting a new web application project — elicit requirements (MoSCoW scoping), create architecture and requirements documents, break work into tasks, and register them as a GitHub Project kanban board. Use when the user says "新しいWebアプリを作りたい", "Webアプリの立ち上げを手伝って", "start a new web app project", "プロジェクトの要件を整理したい", or "GitHub Projectにタスクを登録したい".

This skill should be used when the user asks to "プロジェクトを解析して", "コードベースを調べてドキュメント化して", "移行作業の準備をして", "新機能実装の前にプロジェクトを整理して", "analyze this codebase", "document the project structure", "既存プロジェクトのCLAUDE.mdを作って", or wants to prepare CLAUDE.md and architecture docs before a migration, feature development, or onboarding.

Claude Agent SDK（Python / TypeScript）を使った機能実装の設計をサポートするスキル。 ヒアリング型ワークフローでユーザーの要件を明確化し、 公式ドキュメントに基づいた最適なアーキテクチャと実装パターンを提案する。 Trigger: Agent SDK, claude_agent_sdk, claude-agent-sdk, ClaudeAgentOptions, ClaudeSDKClient, Agent SDKで, エージェントSDK, エージェントを作りたい, agent-sdkを使って, query(), createSdkMcpServer, サブエージェント構成, agent architecture

This skill should be used when the user wants to "stress-test a design", "challenge an idea", "red team a proposal", "get critical feedback on a design", "validate a design", "adversarial architecture review", "risk assessment", "設計を検証して", "反論をもらいたい", "設計を批判的にレビュー", "デビルズアドボケート", "ストレステスト", "弱点を指摘して", "穴を見つけて", "この設計で良いか", "リスク評価", "設計のアーキテクチャレビュー", or mentions structured adversarial review of a proposal or design. NOTE: Use this for validating PROPOSALS and DESIGNS through adversarial debate, NOT for generic code review, PR review, or normal review requests (use /codex:review or /codex:adversarial-review for those). Also NOT for investigating unknown bugs (use /agent-dialectics:strong-inference for that).

Hexagonal Architecture (Ports & Adapters) knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for Hexagonal Architecture audits.

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Layered Architecture knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for traditional N-tier/Layered Architecture audits.

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。

Apply 37signals/DHH Rails conventions when writing Ruby on Rails code. Use when building Rails applications, reviewing Rails code, or making architectural decisions. Covers various aspects of Rails application architecture, design and dependencies.

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。

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.

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 patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical 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。

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.

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。