event-sourcing-cqrs-design
Design event sourcing and/or CQRS. Event store, event schema, aggregate boundaries, projections, consistency, snapshotting, versioning / upcasting, replay, GDPR implications.
What this skill does
# Event Sourcing + CQRS Design
You design event sourcing (state as append-only event log) and/or CQRS (separate command + query models). Often used together but independent patterns.
## When each fits
| Pattern | Use when |
|---|---|
| **CQRS alone** | Different read / write models optimal; no need for audit / replay |
| **Event sourcing alone** | Audit requirements; temporal queries; complex domain logic |
| **Both together** | Domain complex enough for ES + reads diverge from writes |
Both have real cost — don't adopt without justification.
## Event sourcing core
### Events as first-class
- **Events are facts** — happened in the past, immutable
- **Verb-past-tense naming**: "OrderPlaced", "PaymentCaptured", "UserSignedUp"
- **One aggregate per stream** — events for one entity grouped + ordered
- **Append-only** — never update / delete historical events
### Aggregates (from DDD)
Each aggregate = consistency boundary. Events belong to an aggregate stream. Commands validated against current state (replayed from events).
### Event store options
| Option | Best for |
|---|---|
| **EventStoreDB** | Purpose-built for event sourcing |
| **Kafka** | Log-based; long retention possible |
| **Postgres with `events` table** | Simpler; works for low-medium scale |
| **Axon Server** | JVM ecosystem |
| **DynamoDB** | Cloud-native; requires design discipline |
### Event schema
- **Type**: `OrderPlaced.v1`
- **Aggregate ID**: `order-uuid`
- **Sequence number**: per-stream
- **Timestamp**
- **Data**: payload
- **Metadata**: user, correlation ID, causation ID
## CQRS core
### Command side
- Accepts commands (intent to change state)
- Validates against current model
- Produces events (if ES) OR writes to write-model (if non-ES)
- No queries here
### Query side
- Reads from projections / read-models optimized for query patterns
- No commands
- Eventually consistent with write side
### Projections
- Consume events (if ES) or change-log (if non-ES CQRS)
- Build denormalized read-optimized views
- Multiple projections per domain (one per query pattern)
- Rebuildable from scratch (for ES — replay events)
## Consistency
- **Within an aggregate**: strongly consistent (single stream)
- **Across aggregates**: eventually consistent
- **Command → read-model**: eventual (typically < 1s)
Users see eventual consistency; design for it (optimistic UI, read-your-writes session tricks).
## Snapshotting
Rebuilding state by replaying every event is slow for long-lived aggregates. Periodically snapshot state; replay events since last snapshot.
- Snapshot policy: every N events or time-based
- Stored separately; recomputable
## Versioning / upcasting
Event schemas evolve. Strategies:
- **Versioned event types** (`OrderPlaced.v1`, `OrderPlaced.v2`)
- **Upcasting**: transform v1 → v2 on read
- **Never change old events** — only add new versions
## Replay
- Core ES advantage: rebuild any view by replaying events
- Fix a projection bug → drop projection + replay
- Support temporal queries ("what was the state on 2024-06-12?")
## GDPR compliance in immutable stores
Tension: right-to-delete vs immutable events.
Strategies:
- **Crypto-erasure**: encrypt personal data with per-subject key; delete key = data unreadable
- **Redaction events**: emit compensating events removing PII (don't actually delete; mark as unreadable)
- **Separation**: personal data in separate store (deletable); events reference by ID
- **Retention**: delete events after retention period
Choose before first event; retrofit is painful.
## Common anti-patterns
- Using ES for CRUD — overhead without benefit
- Events as "change records" — should be domain facts
- Too-large events (dump entire state) — violates event-as-minimal-fact
- No snapshotting → slow rehydration
- Projections that diverge from events (manual writes) → state drift
## Report
```markdown
# Event Sourcing + CQRS Design: [Domain]
## Scope
[ES scope + CQRS scope + rationale]
## Event Store
[Chosen + rationale]
## Aggregates + Event Schemas
[Per aggregate: events + schemas]
## Command Model
[Validators + event producers]
## Read Models / Projections
[Per query pattern: projection + schema]
## Consistency
[Where strong / where eventual]
## Snapshotting
[Policy]
## Versioning Strategy
[Schema evolution + upcasting]
## Replay Capability
[Use cases + tooling]
## GDPR Compliance
[Strategy for right-to-delete]
## Monitoring
[Event lag / projection health / replay status]
## Diagram
```
## Failure behavior
- ES proposed for simple CRUD → challenge
- No snapshotting → recommend before scale
- GDPR ignored → require strategy
- mmdc failure → see mixin
Related in Design
contribute
IncludedLocal-only OSS contribution command center. Auto-refreshes the user's in-flight PR and issue state on invoke so conversations start with full context — no need to brief Claude on what's in flight. Helps the user find issues to contribute to on GitHub, builds per-repo dossiers of what each upstream expects (CLA, DCO, branch convention, AI policy, draft-first, review bots, issue templates), runs deterministic gates before any external action so AI-assisted contributions don't reach maintainers as slop. State is markdown-only: candidate files at ~/.contribute-system/candidates/, repo dossiers at ~/.contribute-system/research/, append-only event log at ~/.contribute-system/log.jsonl. No database, no cloud calls. Use when the user asks about their PRs / issues / contributions, wants to find new work to take on, claim an issue, build/refresh a repo's dossier, or draft a Design Issue or PR. Trigger with "/contribute", "what's my PR status", "find a contribution", "claim issue X", "draft a Design Issue for Y", "refresh dossier for Z".
architectural-analysis
IncludedUser-triggered deep architectural analysis of a codebase or scoped subtree across eight modes — information architecture, data flow, integration points, UI surfaces, interaction patterns, data model, control flow, and failure modes. This skill should be used when the user asks to "diagram this codebase," "map the architecture," "show the data flow," "give me an ERD," "trace control flow," "find the integration points," "verify the layout pattern," "audit the UX architecture," or any similar request whose primary deliverable is mermaid diagrams plus cited reports under docs/architecture/. Dispatches haiku/sonnet sub-agents in parallel for per-mode exploration, then verifies every citation mechanically before any node lands in a diagram. Not for one-off prose explanations of code (use code-explanation) or for high-level system design from scratch (use system-design).
mcp
IncludedModel Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
react-native-skia
IncludedDesign, build, debug, and optimise high-polish animated graphics in React Native or Expo using @shopify/react-native-skia, Reanimated, and Gesture Handler. Use when the user wants canvas-driven UI, shaders, paths, rich text, image filters, sprite fields, Skottie, video frames, snapshots, web CanvasKit setup, or performance tuning for custom motion-heavy elements such as loaders, hero art, cards, charts, progress indicators, particle systems, or gesture-driven surfaces. Also use when the user asks for fluid, glow, glass, blob, parallax, 60fps/120fps, or GPU-friendly animated effects in React Native, even if they do not explicitly say "Skia". Do not use for ordinary form/layout work with standard views.
plaid
IncludedProduct Led AI Development — guides founders from idea to launched product. Six capabilities: Idea (discover a product idea), Validate (pressure-test the idea against fatal flaws, problem reality, competition, and 2-week MVP feasibility), Plan (vision intake + document generation), Design (translate image references into a design.md spec), Launch (go-to-market strategy), and Build (roadmap execution). Use when someone says "PLAID", "plaid idea", "help me find an idea", "product idea", "idea from my business", "idea from my expertise", "plaid validate", "validate my idea", "pressure-test", "is this idea good", "find fatal flaws", "validate the problem", "plan a product", "define my vision", "generate a PRD", "product strategy", "plaid design", "design from image", "translate image to design", "create design.md", "extract design tokens", "plaid launch", "go-to-market", "launch plan", "GTM strategy", "launch playbook", "plaid build", "build the app", "start building", or "execute the roadmap".
nextjs-framer-motion-animations
IncludedAdds production-safe Motion for React or Framer Motion animations to Next.js apps, including reveal, hover and tap micro-interactions, whileInView, stagger, AnimatePresence, layout and layoutId transitions, reorder, scroll-linked UI, and lightweight route-content transitions. Use when the user asks to add, refactor, or debug Motion or Framer Motion in App Router or Pages Router codebases, especially around server/client boundaries, reduced motion, LazyMotion, bundle size, hydration, or route transitions. Avoid for GSAP-style timelines, WebGL or 3D scenes, heavy scroll storytelling, or CSS-only effects unless Motion is explicitly requested.