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概要と使いどころ
Generates RESTful API Controllers with proper routing, versioning, authorization, and MediatR integration. Follows REST conventions and Clean Architecture patterns.
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Generates CQRS Commands with Handlers, Validators, and Request DTOs following Clean Architecture patterns. Commands represent actions that modify state and return Result types for proper error handling.
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architecture で選定したデータ基盤（Microsoft Fabric / Azure Databricks / Foundry IQ）を、事前確認 → plan と hash 承認 → デプロイ → セマンティック層 → runtime 検証 → 計算停止まで API で構築し、MCP 接続情報を Cowork / Copilot Studio / Foundry へ引き渡す。Dataverse は dataverse スキル、データ投入は data-migration スキルへ委譲する。
Electrical power distribution design for infrastructure: load calculations (NEC 220), conductor sizing (NEC 310.16), transformer/UPS/PDU selection, redundancy architectures (N through 2N+1), DC distribution, and voltage classes 120V-480V. Activates for electrical load calculations, conductor sizing, power equipment selection, data center power design, and redundancy architecture planning.
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Author and manage Architecture Decision Records (ADRs) in docs/specs/. Use when a significant architectural decision needs to be documented.
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Backend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.
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Use when creating a new feature development task — scaffolds a structured task file at .claude/tasks/{feature-name}.md with phased breakdown (Design, Implementation, Testing, Documentation), acceptance criteria, context preservation, and TaskCreate tracking. Activates on "create a feature task", "set up development tracking", "plan a feature implementation", or when preparing work for python-cli-architect or python-pytest-architect agents.
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Use for architecture review, dependency graphs, coupling analysis, or circular dependency detection. Establishes project module namespaces and traces imports plus Claude plugin hook, skill, script, PEP 723, and MCP boundaries. Emits partitioned Mermaid graphs with cycle, coupling, and ownership signals; verifies contract and consequence before assigning severity. Registers diagrams as codebase-analysis artifacts.
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Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.
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Deterministic Software Graph analysis via Ontoly CLI and MCP. Use when: (1) Codebase architecture, dependency, route, service, module, configuration, or impact questions need graph evidence, (2) A repository should be analyzed before source search, (3) You need a persistent SoftwareGraph.json for validation, MCP, or agent workflows. Triggers: "build software graph", "trace route", "impact analysis", "architecture summary", "dependency graph", "what uses this", "Ontoly".
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Use this skill when architecting new Claude Code agents following Anthropic best practices. Guides through YAML frontmatter creation, agent structure definition, role boundaries, and validation. Critical for creating minimal agent files (~150 lines) with proper skill invocations. Examples: <example>Context: User wants to create a new agent for security auditing user: "Create a security-auditor agent" assistant: "I'll use the agent-creator skill to build this agent following Anthropic best practices" <commentary>New agent creation requires the agent-creator skill to ensure proper structure and YAML frontmatter.</commentary></example> <example>Context: Existing agent file is too verbose and needs refactoring user: "The architect agent is 2000 lines, refactor it to minimal structure" assistant: "I'll use the agent-creator skill to refactor this into a minimal ~150 line agent with a separate skill file" <commentary>Agent refactoring requires the agent-creator skill to separate identity from technical procedures.</commentary></example>
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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. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
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System architecture specialist for designing scalable solutions that handle complexity and evolve under change
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Use for "how does X work", code walkthroughs before changing something, and placement / ownership / layering questions ("where should this live", "which package owns this", "is this the right layer"). Explains subsystem architecture, runtime flow, onboarding mental models. Can critique architecture. Use why for motivation.
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Review and refine GitHub Well-Architected Framework (WAF) documentation under the content/ folder for clarity, precision, consistency, and publication readiness. Use this when reviewing pull requests, markdown files, or draft content in content/ to ensure guidance is unambiguous, readable, and aligned with editorial standards.
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Icarus Figures produces publication-grade figures for scientific papers — reproducible matplotlib/seaborn data figures and original TikZ method/framework/architecture figures, held to a four-axis quality bar (depth · elegance · unimpeachable · visible-gap) and exported as editable PDF+PNG+SVG with a runnable critique gate. Use this whenever a figure is destined for a paper, journal, conference submission, thesis, or report — making a plot/chart publication- or journal-ready, building a method/architecture/framework diagram or 技术路线图 (the hero figure a paper opens with), a schematic or workflow figure, or cleaning up a matplotlib/seaborn/TikZ figure that currently looks like a homework plot. Trigger even when the user never says "publication": if the figure goes into a written scientific document, this skill applies.
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Build and query architecture-aware code search, dependency graphs, call flows, impact analysis, and belief maps for Python, TypeScript, TSX, Rust, C#, Java, Go, Ruby, and Ruby on Rails repositories. Use before non-trivial code changes to find module boundaries, blast radius, architecture violations, and the minimal source files to read.
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Evaluate an HLD note against linked ADRs, requirements, and architecture principles across six dimensions
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Analyse architecture diagrams and flowcharts
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Generate changelog for ArchitectKB template contributions
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Visualize system dependencies and relationships
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Analyse files for ArchitectKB template repository suitability
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Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.
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Expert Architecture Decision Record (ADR) creation and lifecycle management based on Olaf Zimmermann's methodology. Use when creating ADRs, reviewing architectural decisions, evaluating decision readiness, writing MADR templates, assessing decision quality, or managing ADR logs. Covers the full lifecycle from readiness (START criteria) through creation, MADR formatting, completion (ECADR criteria), and ongoing maintenance.
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。