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cqrs-event-sourcing

cqrs-event-sourcing

github.com/nickcrewDevelopment6293 installsUpdated 17w ago
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About cqrs-event-sourcing

A guidance skill for teams designing systems with CQRS and Event Sourcing. It covers command/query separation, immutable event histories, projections, consistency, and domain modeling.

Key features

  1. 01Command and query separation
  2. 02Immutable event-based state
  3. 03Read-model projections
  4. 04Consistency and aggregate guidance
  5. 05Reference guides for implementation

Use cases

  1. 01Designing systems with audit trails
  2. 02Querying historical state
  3. 03Scaling distinct read and write workloads
  4. 04Building event-driven applications

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/nickcrew/claude-cortex --skill cqrs-event-sourcing

After installing, type/cqrs-event-sourcingin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
best-practices.md
consistency-patterns.md
cqrs-patterns.md
event-sourcing.md
event-store-tech.md

Details

From the project README

CQRS and Event Sourcing Patterns

Expert guidance for implementing Command Query Responsibility Segregation (CQRS) and Event Sourcing patterns to build scalable, auditable systems with complete historical tracking and optimized read/write models.

When to Use This Skill

  • Building systems requiring complete audit trails and compliance
  • Implementing temporal queries ("show me the state at time T")
  • Designing high-scale applications with complex domain logic
  • Creating systems with significantly different read and write patterns
  • Building event-driven architectures with historical replay capability
  • Implementing systems requiring multiple read model projections
  • Designing applications where understanding "what happened" is critical
  • Building collaborative systems with conflict resolution needs

Core Principles

1. Command Query Separation

Separate operations that change state (commands) from operations that read state (queries).

Commands (Write)Queries (Read)
Express intent (CreateOrder, UpdatePrice)Return data, never change state
Can be rejected (validation failures)Can be cached and optimized
Return success/failure, not dataMultiple models for different needs
Change system stateEventually consistent with writes
2. Events as Source of Truth

Store state changes as immutable events rather than current state snapshots.

Traditional: Store what IS → UPDATE users SET email = '[email protected]' Event Sourcing: Store what HAPPENED → APPEND UserEmailChanged event

Result: Complete history, temporal queries, audit trail

3. Eventual Consistency

Accept temporary inconsistency between write and read models for scalability.

4. Domain-Driven Design Integration
  • Aggregates enforce business invariants
  • Events represent domain facts
  • Commands express domain operations
  • Bounded contexts define consistency boundaries

Quick Reference

TaskLoad reference
CQRS implementation patternsskills/cqrs-event-sourcing/references/cqrs-patterns.md
Event sourcing & snapshotsskills/cqrs-event-sourcing/references/event-sourcing.md
EventStoreDB & Axon Frameworkskills/cqrs-event-sourcing/references/event-store-tech.md
Consistency patternsskills/cqrs-event-sourcing/references/consistency-patterns.md
Best practices checklistskills/cqrs-event-sourcing/references/best-practices.md

Workflow

  1. Identify if CQRS/ES is appropriate (high audit, temporal, or scale needs)
  2. Design commands expressing user intent
  3. Define events as immutable facts (past tense naming)
  4. Implement aggregates as consistency boundaries
  5. Create projections optimized for specific query needs
  6. Handle eventual consistency across bounded contexts

Common Mistakes

  • Using CQRS for simple CRUD applications (overkill)
  • Large aggregates that span multiple consistency boundaries
  • Modifying or deleting events after publication
  • Skipping command validation before aggregate processing
  • Missing idempotency in event handlers
  • No versioning strategy for event schema evolution
  • Tight coupling between aggregates (use ID references only)

Resources

  • Books: "Implementing Domain-Driven Design" (Vernon), "Event Sourcing & CQRS" (Betts et al)
  • Sites: cqrs.wordpress.com, eventstore.com/blog, axoniq.io/resources
  • Tools: EventStoreDB, Axon Framework, Marten, Eventuous
  • Patterns: Event Sourcing, CQRS, Process Manager, Saga, Snapshot

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