Arkhe-claude-plugins domain-driven-design

Expert guidance for Domain-Driven Design architecture and implementation. Use when designing complex business systems, defining bounded contexts, structuring domain models, choosing between modular monolith vs microservices, implementing aggregates/entities/value objects, or when users mention "DDD", "domain-driven design", "bounded context", "aggregate", "domain model", "ubiquitous language", "event storming", "context mapping", "domain events", "anemic domain model", strategic design, tactical patterns, or domain modeling. Helps make architectural decisions, identify subdomains, design aggregates, and avoid common DDD pitfalls.

install

source · Clone the upstream repo

git clone https://github.com/joaquimscosta/arkhe-claude-plugins

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/joaquimscosta/arkhe-claude-plugins "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/spring-boot/skills/domain-driven-design" ~/.claude/skills/joaquimscosta-arkhe-claude-plugins-domain-driven-design && rm -rf "$T"

manifest: plugins/spring-boot/skills/domain-driven-design/SKILL.md

source content

Domain-Driven Design Skill

DDD manages complexity through alignment between software and business reality. Strategic design (boundaries, language, subdomains) provides more value than tactical patterns (aggregates, repositories).

When to Apply DDD

Apply DDD when:

Domain has intricate business rules
System is long-lived and high-value
Domain experts are available
Multiple teams/departments involved
Software represents competitive advantage

DDD is overkill when:

Simple CRUD applications
Tight deadlines, limited budgets
No domain experts available
Complexity is purely technical, not business

Core Workflow

Domain Discovery → 2. Bounded Context Definition → 3. Context Mapping → 4. Architecture Selection → 5. Tactical Implementation

See WORKFLOW.md for detailed step-by-step instructions for each phase.

Quick Reference

Subdomain Types (Problem Space)

Type	Investment	Example
Core	Maximum - competitive advantage	Recommendation engine, trading logic
Supporting	Custom but quality tradeoffs OK	Inventory management
Generic	Buy/outsource	Auth, email, payments

Key Decision: Entity vs Value Object

Entity: Has identity, tracked through time, mutable →
```
Customer
```
,
```
Order
```
Value Object: Defined by attributes, immutable, interchangeable →
```
Money
```
,
```
Address
```
,
```
Email
```

Default to value objects. Only use entities when identity matters.

Aggregate Design Rules (Vaughn Vernon)

Model true invariants in consistency boundaries
Design small aggregates (~70% should be root + value objects only)
Reference other aggregates by ID only
Use eventual consistency outside the boundary

Architecture Decision

Start with modular monolith when:
├── Team < 20 developers
├── Domain boundaries unclear
├── Time-to-market critical
└── Strong consistency required

Consider microservices when:
├── Bounded contexts have distinct languages
├── Teams can own full contexts
├── Independent scaling required
└── DevOps maturity exists

Detailed References

Strategic Patterns: See references/STRATEGIC-PATTERNS.md for subdomains, bounded contexts, context mapping, event storming
Tactical Patterns: See references/TACTICAL-PATTERNS.md for entities, value objects, aggregates, services, repositories
Architecture Alignment: See references/ARCHITECTURE-ALIGNMENT.md for clean/hexagonal architecture, modular monolith, microservices
Workflow: See WORKFLOW.md for detailed step-by-step DDD implementation process
Anti-Patterns: See references/ANTI-PATTERNS.md for common pitfalls and how to avoid them
Examples: See EXAMPLES.md for scenario walkthroughs applying DDD concepts
Troubleshooting: See TROUBLESHOOTING.md for common issues and solutions

Critical Reminders

Ubiquitous language first - Code should read like business language
Strategic before tactical - Understand boundaries before implementing patterns
Apply tactical patterns selectively - Only in core domains where complexity warrants
One aggregate per transaction - Cross-aggregate consistency via domain events
Persistence ignorance - Domain layer has no infrastructure dependencies

Related Skills

Need	Skill
Data layer implementation	`spring-boot-data-ddd` — JPA/JDBC aggregates, repositories, transactions
REST API layer	`spring-boot-web-api` — Controllers, validation, exception handling
Module boundaries	`spring-boot-modulith` — Module structure, event-driven communication
Testing patterns	`spring-boot-testing` — Aggregate tests, module tests, Scenario API
Security for domains	`spring-boot-security` — Method-level authorization, role-based access