# Clean Architecture > Clean Architecture guidance centered on the dependency rule, entities, use cases/interactors, and interface adapters that keep business policy independent from frameworks, databases, and UI. Use when the main design question is how policy flows through use cases and adapter boundaries. Use hexagonal-architecture when named inbound/outbound ports around external actors are the main concern, onion-architecture when explicit concentric domain/application rings are the requested model, and architecture-review for a read-only audit. Do not use for simple CRUD, prototypes, or framework-convention-first apps where added layers reduce clarity. - Skill: `nledford/clean-architecture` (Agent Skill) - Install (CLI): `npx skillmds@latest add nledford/clean-architecture` - Raw SKILL.md: https://api.skillmd.com/api/skills/nledford/clean-architecture/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: nledford (https://skillmd.com/u/nledford) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/nledford/clean-architecture --- # Clean Architecture Use Clean Architecture to keep business policy independent from delivery mechanisms, frameworks, databases, UI, queues, and vendor SDKs. The core idea is separation of concerns enforced by the dependency rule: source-code dependencies point inward toward higher-level policy, while outer details adapt to the core. Clean Architecture is a dependency strategy, not a mandatory folder layout. Apply it only where business rules, lifetime, testability, or change pressure justify the ceremony. ## Use When Recommend or apply Clean Architecture when the work involves: - Long-lived services or applications where maintainability matters more than fastest initial delivery. - Complex business rules, invariants, workflows, policies, or application use cases that should survive framework, UI, database, or vendor changes. - Multiple delivery mechanisms invoking the same behavior: HTTP, CLI, jobs, schedulers, message consumers, server functions, UI actions, or APIs. - Infrastructure that should be replaceable or testable behind seams: databases, ORMs, queues, caches, clocks, ID generators, file systems, cloud SDKs, payment providers, email senders, or external services. - Teams that can tolerate explicit boundaries, mapping, tests per boundary, and the learning curve of dependency inversion. Do not force it for: - Simple CRUD with little business behavior. - Prototypes, one-off scripts, throwaway tools, migrations, or small automation. - Apps where framework conventions are intentionally the architecture. - Teams or deadlines where extra indirection will slow learning and reduce clarity more than it protects future change. - Features that might grow later but do not yet have real policy, external mechanisms, or testability pressure. Leave seams; do not build unused layers. ## Dependency Rule - Inner policy must not mention outer details: frameworks, controllers, request objects, response objects, ORM rows, database clients, SDK models, queues, serializer types, or UI components. - Outer layers depend on inner layers. If control must flow outward, use dependency inversion: define the needed boundary in or near the inner policy and implement it outward. - Data crossing inward should be simple and shaped for the inner use case, not a framework, persistence, transport, or vendor format. - The dependency rule matters more than the number or names of layers. Four circles are a teaching diagram, not a required package count. ## Typical Responsibilities - **Entities/domain model:** general business rules, invariants, calculations, state transitions, policies, value objects, aggregates, and domain events. They should be independent of application workflow and infrastructure details. - **Use cases/interactors/application services:** application-specific business rules. They orchestrate workflows, authorization handoff, transactions, entity/domain operations, outbound gateway calls, and result production. - **Interface adapters:** controllers, presenters, view models, serializers, repository/gateway implementations, persistence mappers, API clients, queue consumers/producers, and adapters that translate between inner models and outer mechanisms. - **Frameworks, drivers, and infrastructure:** web frameworks, databases, ORMs, UI frameworks, message brokers, file systems, cloud services, external SDKs, app startup, dependency injection wiring, and glue code. Names vary by ecosystem. `use case`, `interactor`, `application service`, `handler`, or `command handler` can all be valid if dependency direction and responsibility boundaries are clear. ## Workflow 1. **Confirm the cost is justified.** Identify the business policy, expected lifetime, change pressure, delivery mechanisms, infrastructure dependencies, and tests that need isolation. If these are weak, recommend a simpler design. 2. **Evaluate the existing architecture first.** Inspect modules, dependencies, tests, framework conventions, and where business rules currently live. Do not recommend a rewrite or terminology change when healthy inward dependencies already exist. 3. **Choose the smallest scope.** Apply Clean Architecture at a service, module, package, feature area, or bounded context. Do not reorganize the whole repository when one core workflow needs protection. 4. **Name the inner policy.** Put enterprise/application business rules in domain objects and use cases. Keep controllers, ORM models, serializers, queue handlers, and UI components thin translators. 5. **Define boundaries from core needs.** Create input/output boundaries, repository interfaces, gateways, presenters, or ports only where the use case needs a seam. Do not mirror a framework or SDK API inward. 6. **Map at the edges.** Convert request DTOs, API payloads, database rows, persistence models, SDK objects, framework errors, and transport responses at adapter boundaries. Keep business decisions out of mapping code. 7. **Wire dependencies at the outside.** Use dependency injection, composition roots, factories, or module wiring outside the core. The core should receive abstractions or simple functions, not construct infrastructure. 8. **Adopt incrementally.** Move one use case or boundary at a time, protect it with tests, and leave stable code alone. Prefer strangling infrastructure leaks over broad directory reshuffles. When implementation begins, load the matching language engineering skill and any data skill needed for persistence, schema, query, or transaction work. ## Verification And Reporting Before reporting completion, check the changed behavior and dependency direction at the affected policy and adapter boundaries, then run broader repository checks when the change warrants them. Report failures, skipped checks, and residual risk from unverified wiring, mappings, or dependency leaks. ## Boundary and Data Guidance - DTOs are boundary messages. They are not domain entities, ORM rows, API models, or view models unless the project has deliberately collapsed a boundary. - Entities should not depend on persistence annotations, framework base classes, request/session objects, or database row shapes when those details can change independently of policy. - Use case inputs should express what the use case needs, not the raw HTTP body, CLI args, queue payload, or UI form state. - Use case outputs can be simple result DTOs, domain results, events, or an output port/presenter interface. Prefer the simplest shape that preserves inward dependencies and keeps presentation policy outside the use case. - Repository and gateway abstractions should describe domain/application needs: `load_order_for_checkout`, `save_invoice`, or `reserve_credit`, not generic table-shaped CRUD unless generic CRUD is truly the policy. - CQRS is optional. Split commands and queries when read and write concerns, models, scaling, authorization, or performance differ enough to justify it; do not add buses or handlers just to look architectural. ## Testing Guidance - Test entities and domain services directly for invariants, calculations, policies, and state transitions. - Test use cases with fake or in-memory gateways, repositories, presenters, clocks, ID generators, and external-service ports. - Test interface adapters against their real contracts: HTTP routing and serialization, database mappings and constraints, SQL, queue payloads, SDK error mapping, dependency-injection wiring, and framework integration. - Add architecture/dependency tests when the language or tooling can enforce inward dependencies cheaply. - Use end-to-end tests for critical wiring and behavior that narrower tests cannot prove; do not make E2E the only protection for business rules. ## Organization Guidance There is no universal folder structure. Choose a structure that makes dependency direction and domain intent visible in the target language: - For small scoped adoption, organize by feature or bounded context first, then by inner policy versus adapters inside that scope. - For ecosystems that favor projects/packages/modules, make compile-time dependencies enforce the dependency rule where practical. - For framework-heavy apps, keep framework entry points at the edge and move only policy-heavy behavior behind use cases; do not fight every framework convention when the framework is intentionally the product shell. - Prefer names from the domain and use cases over generic buckets like `helpers`, `managers`, or `services` when the code represents business behavior. ## Relationship To Other Architecture Skills - **Layered architecture:** layered systems often separate UI, business, and data access by horizontal layers, but dependencies may point downward into data access. Clean Architecture inverts dependencies so business policy does not depend on data or framework details. - **Hexagonal Architecture:** both protect the core with inward dependencies. Load [`hexagonal-architecture`](../hexagonal-architecture/SKILL.md) when the main decision is ports/adapters around external actors, multiple drivers, swappable infrastructure, or running the core headless. Prefer Clean Architecture wording when the main decision is concentric policy/detail layers, use-case boundaries, interactors, presenters, and interface-adapter responsibilities. Either is fine when the current code already has healthy boundaries; do not rename architecture for terminology alone. - **Onion Architecture:** closely related; both place domain/application policy at the center and infrastructure outside. Load [`onion-architecture`](../onion-architecture/SKILL.md) when the user asks for Onion by name or when domain/application rings are the clearest framing. Prefer Clean Architecture wording when use cases, interactors, presenters, and interface adapters are the clearer responsibilities. - **DDD:** DDD defines ubiquitous language, bounded contexts, aggregates, value objects, repositories, domain services, and invariants. Load [`domain-driven-design`](../domain-driven-design/SKILL.md) when the model and language need work; use Clean Architecture to protect that model and route use cases around it. - **CQRS:** CQRS can fit inside Clean Architecture when separate command and query models solve real complexity. It is not required, and it does not replace the dependency rule. ## Agent Guidance - Before recommending Clean Architecture, ask or infer: expected lifetime, business-rule complexity, delivery mechanisms, infrastructure volatility, testing pain, team familiarity, and whether the user wants architecture change or a local fix. - Caution against Clean Architecture when the request is simple CRUD, a prototype, a framework tutorial, a one-off script, or a small change in an intentionally framework-centric app. - Propose incremental refactors: extract one use case, introduce one boundary, isolate one external dependency, or move one business rule out of a controller. Avoid big-bang rewrites. - Explain tradeoffs explicitly: more files, mapping, abstractions, and onboarding cost in exchange for clearer policy boundaries, testability, and replaceable details. - Preserve repository conventions. Adapt vocabulary to the codebase instead of imposing Clean Architecture names everywhere. ## Common Mistakes - Treating Clean Architecture as folders named `domain`, `application`, `infrastructure`, and `presentation` while dependencies still point outward. - Adding interfaces for every class without a real boundary, alternate implementation, testing seam, or external mechanism to isolate. - Putting business rules in controllers, ORM models, serializers, UI components, queue handlers, database triggers, or framework services by default. - Letting use cases depend on HTTP, ORM, SQL, queue, session, UI, or SDK types. - Passing database rows, active records, framework request objects, or external API payloads inward as if they were domain types. - Confusing DTOs, entities, persistence models, API models, and view models. - Creating an anemic domain model when rich domain behavior would protect invariants better. - Applying the pattern uniformly across every feature regardless of complexity. ## Successful Use The final design names the protected business policy, use cases, entities/domain objects, boundary interfaces, adapters, mapping points, dependency direction, tests per boundary, and any deliberate decision to keep a simpler structure. ## Source Anchors - Robert C. Martin, [The Clean Architecture](https://blog.cleancoder.com/uncle-bob/2012/08/13/the-clean-architecture.html). - Alistair Cockburn, [Hexagonal architecture](https://alistair.cockburn.us/hexagonal-architecture). - Jeffrey Palermo, [The Onion Architecture](https://jeffreypalermo.com/2008/07/the-onion-architecture-part-1/).