What problem does it solve? It provides a complete implementation pattern for systems that must derive state from an immutable sequence of events rather than overwriting current state, enabling full audit logs, temporal queries, and rebuildable read models. ## Core Features & Use Cases - Domain Event Definitions: Immutable, past-tense event classes (OrderPlaced, PaymentProcessed) built with frozen Python dataclasses. - Aggregate & Event Store: An order aggregate enforcing business invariants plus a PostgreSQL-backed append-only event store with optimistic concurrency via expected_version checks. - Projections & CQRS: Denormalized read models built from event streams that can be truncated and rebuilt by replaying the full event history. - Use Case: A fintech team needs a complete audit trail for payment orders. Use this Skill to design the event schema, implement the aggregate and event store, and build a queryable order read model that can be rebuilt at any time. ## Quick Start Ask the AI to design an event-sourced order system with an OrderPlaced event, an aggregate enforcing state transitions, and a PostgreSQL event store with optimistic concurrency.