Query-Specific Repositories vs Generic CRUD Volume 07 - Advanced Application Architecture | Phase 24
The generic repository trap Generic repository trap
find / create / update / delete listScoped / findContext / create
Mirrors ORM and hides useful query semantics Names persistence operations the service actually needs
Generic wrapper example interface Repository<T> { findAll(): Promise<T[]> findById(id: string): Promise<T | null> create(data: Partial<T>): Promise<T> update(id: string, data: Partial<T>): Promise<T> delete(id: string): Promise<void> }
Why it often fails This contract is so broad that complex filtering, scoped authorization, relations, partial updates, transactions, bulk operations, and database-specific capabilities soon leak through anyway. It often recreates a weaker ORM on top of a stronger ORM.
Prefer feature semantics • listScoped(userId, query)
• findForAssignment(taskId)
• findByIdInWorkspace(taskId, workspaceId)
• createFromProject(projectId, data)
Not every query needs a repository method If a one-off reporting query appears later, evaluate it independently. A read-model/query service may be clearer than bloating TaskRepository with unrelated analytics.
Query Specific Repositories vs Generic CRUD matters because it changes a real boundary in TaskFlow. The goal is to understand the inputs, owner, observable output, and failure modes before adding more abstraction.
Restate the goal of “Query Specific Repositories vs Generic CRUD” as one observable behavior. Write the success signal before touching code.
Trace the boundary map: service intent → repository contract → adapter → Prisma/Postgres → domain result. Mark the one boundary this lesson changes.
Inspect the current repository state and record the exact files, route, table, or runtime involved. Avoid creating an abstraction before you can name the existing owner.
Implement the smallest vertical slice. Add one coherent change, run the narrowest verification command, and read the output before continuing.
Connect the slice to TaskFlow’s phase artifact: One TaskFlow aggregate/use case refactored behind a purposeful repository interface with real database integration tests.. Verify behavior from the outside as a user or API client would.
Create one controlled failure that is safe to reproduce. Predict the symptom first, capture evidence, locate the earliest broken boundary, then fix only that cause.
Close the reference and rebuild or explain the core change from memory. Record what you would monitor or test before trusting the same change in production.
export interface TaskRepository {
findById(id: string): Promise<Task | null>;
listForWorkspace(input: TaskListQuery): Promise<TaskPage>;
save(task: Task): Promise<void>;
}Do not copy this as a finished answer. Predict what each boundary does, type the smallest useful slice, run it, then compare the result with your prediction.
Return to the nearest observable boundary: input, network, process log, database, or rendered UI. Compare actual evidence with the predicted path.
Change one variable at a time and reproduce the original failure after the fix; otherwise you have correlation, not diagnosis.
Without copying the final source, create a second small scenario that applies “Query Specific Repositories vs Generic CRUD” to a different TaskFlow resource or input. Write the acceptance criteria first, implement it, and provide the evidence that each criterion is satisfied.
Choose a service whose persistence queries are complex enough to justify a boundary.
Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.Mocks proving an imaginary database behavior
Predict the symptom before causing the failure. Then locate the earliest boundary where reality diverges from expectation.Why does this responsibility live here, what input does it trust, what output proves success, and what would go wrong if another layer owned it?
If your explanation is vague, repeat the boundary trace before moving on.Close the reference. Reproduce the core idea from memory or explain the exact request/data flow aloud. Then check your diff or notes for accidental shortcuts that bypass validation, authorization, error handling, or verification earned in earlier phases.