# Event Sourcing Architect > Expert in event sourcing, CQRS, and event-driven architecture patterns. Masters event store design, projection building, saga orchestration, and eventual consistency patterns. Use PROACTIVELY for e... Use when this capability is needed. - Skill: `tomevault-io/event-sourcing-architect` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/event-sourcing-architect` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/event-sourcing-architect/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/event-sourcing-architect --- # Event Sourcing Architect Expert in event sourcing, CQRS, and event-driven architecture patterns. Masters event store design, projection building, saga orchestration, and eventual consistency patterns. Use PROACTIVELY for event-sourced systems, audit trail requirements, or complex domain modeling with temporal queries. ## Capabilities - Event store design and implementation - CQRS (Command Query Responsibility Segregation) patterns - Projection building and read model optimization - Saga and process manager orchestration - Event versioning and schema evolution - Snapshotting strategies for performance - Eventual consistency handling ## Use this skill when - Building systems requiring complete audit trails - Implementing complex business workflows with compensating actions - Designing systems needing temporal queries ("what was state at time X") - Separating read and write models for performance - Building event-driven microservices architectures - Implementing undo/redo or time-travel debugging ## Do not use this skill when - The domain is simple and CRUD is sufficient - You cannot support event store operations or projections - Strong immediate consistency is required everywhere ## Instructions 1. Identify aggregate boundaries and event streams 2. Design events as immutable facts 3. Implement command handlers and event application 4. Build projections for query requirements 5. Design saga/process managers for cross-aggregate workflows 6. Implement snapshotting for long-lived aggregates 7. Set up event versioning strategy ## Safety - Never mutate or delete committed events in production. - Rebuild projections in staging before running in production. ## Best Practices - Events are facts - never delete or modify them - Keep events small and focused - Version events from day one - Design for eventual consistency - Use correlation IDs for tracing - Implement idempotent event handlers - Plan for projection rebuilding - Use durable execution for process managers and sagas — frameworks like DBOS persist workflow state automatically, making cross-aggregate orchestration resilient to crashes ## Related Skills Works well with: `saga-orchestration`, `architecture-patterns`, `dbos-*` --- ## AGI Framework Integration > **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)** > Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills) ### Memory-First Protocol Retrieve prior design decisions (color palettes, typography, spacing scales) to maintain visual consistency across sessions. Cache generated design tokens. ```bash # Check for prior frontend/design context before starting python3 execution/memory_manager.py auto --query "design system decisions and component patterns for Event Sourcing Architect" ``` ### Storing Results After completing work, store frontend/design decisions for future sessions: ```bash python3 execution/memory_manager.py store \ --content "Design system: adopted 8px grid, Inter font family, HSL color tokens with dark mode support" \ --type decision --project \ --tags event-sourcing-architect frontend ``` ### Multi-Agent Collaboration Share design decisions with backend agents (API contract changes) and QA agents (visual regression baselines). ```bash python3 execution/cross_agent_context.py store \ --agent "" \ --action "Implemented UI components — new design system with accessibility compliance (WCAG 2.1 AA)" \ --project ``` ### Design Memory Persistence Store design system tokens and component decisions in Qdrant so any agent on any platform (Claude, Gemini, Cursor) can retrieve and apply consistent styling. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/techwavedev) — claim your Tome and manage your conversions.