Agent skill
domain-driven-design
Domain-Driven Design tactical patterns for complex business domains. Use when modeling entities, value objects, domain services, repositories, or establishing bounded contexts.
Install this agent skill to your Project
npx add-skill https://github.com/yonatangross/orchestkit/tree/main/src/skills/domain-driven-design
Metadata
Additional technical details for this skill
- category
- document-asset-creation
SKILL.md
Domain-Driven Design Tactical Patterns
Model complex business domains with entities, value objects, and bounded contexts.
Overview
- Modeling complex business logic
- Separating domain from infrastructure
- Establishing clear boundaries between subdomains
- Building rich domain models with behavior
- Implementing ubiquitous language in code
Building Blocks Overview
┌─────────────────────────────────────────────────────────────┐
│ DDD Building Blocks │
├─────────────────────────────────────────────────────────────┤
│ ENTITIES VALUE OBJECTS AGGREGATES │
│ Order (has ID) Money (no ID) [Order]→Items │
│ │
│ DOMAIN SERVICES REPOSITORIES DOMAIN EVENTS │
│ PricingService IOrderRepository OrderSubmitted │
│ │
│ FACTORIES SPECIFICATIONS MODULES │
│ OrderFactory OverdueOrderSpec orders/, payments/ │
└─────────────────────────────────────────────────────────────┘
Quick Reference
Entity (Has Identity)
from dataclasses import dataclass, field
from uuid import UUID
from uuid_utils import uuid7
@dataclass
class Order:
"""Entity: Has identity, mutable state, lifecycle."""
id: UUID = field(default_factory=uuid7)
customer_id: UUID = field(default=None)
status: str = "draft"
def __eq__(self, other: object) -> bool:
if not isinstance(other, Order):
return NotImplemented
return self.id == other.id # Identity equality
def __hash__(self) -> int:
return hash(self.id)
Load Read("${CLAUDE_SKILL_DIR}/references/entities-value-objects.md") for complete patterns.
Value Object (Immutable)
from dataclasses import dataclass
from decimal import Decimal
@dataclass(frozen=True) # MUST be frozen!
class Money:
"""Value Object: Defined by attributes, not identity."""
amount: Decimal
currency: str
def __add__(self, other: "Money") -> "Money":
if self.currency != other.currency:
raise ValueError("Cannot add different currencies")
return Money(self.amount + other.amount, self.currency)
Load Read("${CLAUDE_SKILL_DIR}/references/entities-value-objects.md") for Address, DateRange examples.
Key Decisions
| Decision | Recommendation |
|---|---|
| Entity vs VO | Has unique ID + lifecycle? Entity. Otherwise VO |
| Entity equality | By ID, not attributes |
| Value object mutability | Always immutable (frozen=True) |
| Repository scope | One per aggregate root |
| Domain events | Collect in entity, publish after persist |
| Context boundaries | By business capability, not technical |
Rules Quick Reference
| Rule | Impact | What It Covers |
|---|---|---|
aggregate-boundaries (load ${CLAUDE_SKILL_DIR}/rules/aggregate-boundaries.md) |
HIGH | Aggregate root design, reference by ID, one-per-transaction |
aggregate-invariants (load ${CLAUDE_SKILL_DIR}/rules/aggregate-invariants.md) |
HIGH | Business rule enforcement, specification pattern |
aggregate-sizing (load ${CLAUDE_SKILL_DIR}/rules/aggregate-sizing.md) |
HIGH | Right-sizing, when to split, eventual consistency |
When NOT to Use
Under 5 entities? Skip DDD entirely. The ceremony costs more than the benefit.
| Pattern | Interview | Hackathon | MVP | Growth | Enterprise | Simpler Alternative |
|---|---|---|---|---|---|---|
| Aggregates | OVERKILL | OVERKILL | OVERKILL | SELECTIVE | APPROPRIATE | Plain dataclasses with validation |
| Bounded contexts | OVERKILL | OVERKILL | OVERKILL | BORDERLINE | APPROPRIATE | Python packages with clear imports |
| CQRS | OVERKILL | OVERKILL | OVERKILL | OVERKILL | WHEN JUSTIFIED | Single model for read/write |
| Value objects | OVERKILL | OVERKILL | BORDERLINE | APPROPRIATE | REQUIRED | Typed fields on the entity |
| Domain events | OVERKILL | OVERKILL | OVERKILL | SELECTIVE | APPROPRIATE | Direct method calls between services |
| Repository pattern | OVERKILL | OVERKILL | BORDERLINE | APPROPRIATE | REQUIRED | Direct ORM queries in service layer |
Rule of thumb: DDD adds ~40% code overhead. Only worth it when domain complexity genuinely demands it (5+ entities with invariants spanning multiple objects). A CRUD app with DDD is a red flag.
Anti-Patterns (FORBIDDEN)
# NEVER have anemic domain models (data-only classes)
@dataclass
class Order:
id: UUID
items: list # WRONG - no behavior!
# NEVER leak infrastructure into domain
class Order:
def save(self, session: Session): # WRONG - knows about DB!
# NEVER use mutable value objects
@dataclass # WRONG - missing frozen=True
class Money:
amount: Decimal
# NEVER have repositories return ORM models
async def get(self, id: UUID) -> OrderModel: # WRONG - return domain!
Related Skills
aggregate-patterns- Deep dive on aggregate designork:distributed-systems- Cross-aggregate coordinationork:database-patterns- Schema design for DDD
References
Load on demand with Read("${CLAUDE_SKILL_DIR}/references/<file>"):
| File | Content |
|---|---|
entities-value-objects.md |
Full entity and value object patterns |
repositories.md |
Repository pattern implementation |
domain-events.md |
Event collection and publishing |
bounded-contexts.md |
Context mapping and ACL |
Capability Details
entities
Keywords: entity, identity, lifecycle, mutable, domain object Solves: Model entities in Python, identity equality, adding behavior
value-objects
Keywords: value object, immutable, frozen, dataclass, structural equality Solves: Create immutable value objects, when to use VO vs entity
domain-services
Keywords: domain service, business logic, cross-aggregate, stateless Solves: When to use domain service, logic spanning aggregates
repositories
Keywords: repository, persistence, collection, IRepository, protocol Solves: Implement repository pattern, abstract DB access, ORM mapping
bounded-contexts
Keywords: bounded context, context map, ACL, subdomain, ubiquitous language Solves: Define bounded contexts, integrate with ACL, context relationships
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
expect
Diff-aware AI browser testing — analyzes git changes, generates targeted test plans, and executes them via agent-browser. Reads git diff to determine what changed, maps changes to affected pages via route map, generates a test plan scoped to the diff, and runs it with pass/fail reporting. Use when testing UI changes, verifying PRs before merge, running regression checks on changed components, or validating that recent code changes don't break the user-facing experience.
github-operations
GitHub CLI operations for issues, PRs, milestones, and Projects v2. Covers gh commands, REST API patterns, and automation scripts. Use when managing GitHub issues, PRs, milestones, or Projects with gh.
chain-patterns
Chain patterns for CC 2.1.71 pipelines — MCP detection, handoff files, checkpoint-resume, worktree agents, CronCreate monitoring. Use when building multi-phase pipeline skills. Loaded via skills: field by pipeline skills (fix-issue, implement, brainstorm, verify). Not user-invocable.
storybook-mcp-integration
Storybook MCP server integration for component-aware AI development. Covers 6 tools across 3 toolsets (dev, docs, testing): component discovery via list-all-documentation/get-documentation, story previews via preview-stories, and automated testing via run-story-tests. Use when generating components that should reuse existing Storybook components, running component tests via MCP, or previewing stories in chat.
component-search
Search 21st.dev component registry for production-ready React components. Finds components by natural language description, filters by framework and style system, returns ranked results with install instructions. Use when looking for UI components, finding alternatives to existing components, or sourcing design system building blocks.
ai-ui-generation
AI-assisted UI generation patterns for json-render, v0, Bolt, and Cursor workflows. Covers prompt engineering for component generation, review checklists for AI-generated code, design token injection, refactoring for design system conformance, and CI gates for quality assurance. Use when generating UI components with AI tools, rendering multi-surface MCP visual output, reviewing AI-generated code, or integrating AI output into design systems.
Didn't find tool you were looking for?