event-store-design

Overview of event-store-design skill

What event-store-design is for

The event-store-design skill helps you design the storage layer for event-sourced systems: stream structure, append rules, ordering, concurrency, snapshots, metadata, subscriptions, and operational tradeoffs. It is most useful when you already know you want event sourcing, but need a concrete event store design that will survive real write load, replay needs, and long-term evolution.

Best-fit users and teams

This event-store-design skill is best for backend engineers, architects, and technical leads working on:

• event-sourced services
• CQRS systems with durable event history
• custom event store implementations
• migrations from CRUD persistence to append-only streams
• technology selection for event storage infrastructure

If you are deciding how aggregates map to streams, how optimistic concurrency should work, or how consumers read from a global sequence, this skill is a strong fit.

Real job-to-be-done

Users rarely need theory alone. They need a design that answers practical questions such as:

• what is the stream key for each aggregate
• how events are appended safely under concurrent writes
• whether to use per-stream ordering, global ordering, or both
• how replays, snapshots, and subscriptions affect schema choices
• what metadata must be stored from day one to avoid painful retrofits

That is where event-store-design adds value over a generic architecture prompt.

What makes this skill different

The main differentiator is scope discipline. Instead of discussing event sourcing at a high level, the skill focuses on the event store itself: architecture, requirements, and implementation choices. That makes it especially useful for Backend Development teams that need a design artifact, not a broad primer.

What it does not do well

This skill is less useful if you are still deciding whether event sourcing is appropriate at all, or if you mainly need domain event modeling rather than event store mechanics. It also appears to be documentation-only, with no helper scripts or reference files, so output quality depends heavily on how specific your prompt is.

How to Use event-store-design skill

How to install event-store-design

Use the standard skills installer from the repository ecosystem:

npx skills add https://github.com/wshobson/agents --skill event-store-design

Because the skill folder only exposes SKILL.md, installation is lightweight. There are no extra scripts, resources, or rule files to configure.

Where to read first after install

Start with:

• SKILL.md

Since this skill has no supporting files, read it top to bottom once. The most decision-relevant sections are the usage criteria, event store architecture, and requirements guidance.

What input the skill needs to work well

The event-store-design usage quality depends on the design constraints you provide. Include:

• domain and aggregate boundaries
• expected write and read volume
• concurrency profile
• retention and replay needs
• consistency expectations
• subscription or projection requirements
• cloud, database, and ops constraints
• compliance or audit requirements

Without these inputs, the output will tend to stay generic.

Turn a rough goal into a strong prompt

Weak prompt:

Design an event store for my app.

Stronger prompt:

Use the event-store-design skill to design an event store for an order management system. We have aggregates for Order, Payment, and Shipment. Peak write rate is 2k events/sec. We need optimistic concurrency per aggregate, durable audit history, replayable projections, GDPR-aware metadata handling, and cross-stream consumers for analytics. Our stack is PostgreSQL on AWS. Recommend stream structure, event envelope, indexing, snapshot strategy, global ordering approach, and subscription model, with tradeoffs.

The stronger version gives the skill enough context to make real architecture choices.

Prompt template for event-store-design for Backend Development

Use a prompt structure like this:

Use the event-store-design skill.

Context:
- Domain:
- Main aggregates:
- Current persistence model:
- Expected writes/sec:
- Read patterns:
- Replay needs:
- Concurrency expectations:
- Required guarantees:
- Infra constraints:
- Compliance/security constraints:

Deliver:
- Recommended event store architecture
- Stream design
- Event schema and metadata fields
- Concurrency and versioning approach
- Snapshot policy
- Subscription/read model approach
- Operational risks and tradeoffs

This format usually produces better output than asking for “best practices” alone.

Practical workflow that reduces guesswork

A good workflow for event-store-design guide use is:

1. Define whether streams are per aggregate, per tenant, or mixed.
2. List the commands that produce events and where concurrency conflicts happen.
3. Clarify whether consumers need a global position.
4. Ask the skill for a first-pass architecture with tradeoffs.
5. Follow up with edge cases: replays, schema evolution, idempotency, deletes, and snapshots.
6. Ask for a final design narrowed to your chosen storage technology.

This staged approach works better than one giant prompt because event store design is full of tradeoffs.

What to ask for explicitly

The skill is more useful when you ask it to decide, not just describe. Good asks include:

• choose between database-backed and dedicated event store approaches
• recommend event envelope fields
• define append API semantics
• design optimistic concurrency checks
• specify stream naming conventions
• propose indexing for stream reads and global subscriptions
• explain snapshot trigger rules
• identify failure modes under replay and backfill

These are the decisions that usually block implementation.

Likely output areas you should validate

Before adopting the design, check whether the output covers:

• stream identity and partitioning
• per-stream versioning
• global ordering requirements
• append atomicity
• idempotency strategy
• event metadata
• snapshot policy
• subscription checkpointing
• schema evolution and upcasting
• operational observability

If several of these are missing, rerun the prompt with explicit requirements.

Common adoption blockers

The main blockers for event-store-design install decisions are not installation complexity but architectural ambiguity:

• team is new to event sourcing
• aggregate boundaries are unstable
• required guarantees are underspecified
• storage technology is already fixed but poorly suited
• replay cost and projection lag were not considered early

If those issues exist, use the skill to expose tradeoffs first, not to force a premature implementation plan.

When this skill beats a generic prompt

Use event-store-design instead of an ordinary prompt when you need focused guidance on event store internals. A generic LLM prompt often drifts into CQRS theory or domain events. This skill keeps attention on event storage structure and requirements, which is usually the harder adoption step.

event-store-design skill FAQ

Is event-store-design good for beginners?

Yes, if you already understand basic event sourcing concepts. It gives structure to the event store design problem, but it is not a full beginner course. Newer teams may need to pair it with separate guidance on aggregates, commands, and projections.

Does event-store-design choose a specific database?

Not by itself. The skill is better viewed as a design framework than a vendor-specific implementation manual. If you want actionable output, include your target stack, such as PostgreSQL, DynamoDB, or EventStoreDB, in the prompt.

Can I use event-store-design for an existing system migration?

Yes. It is useful for planning a transition from state-based persistence to append-only history, especially when you need to preserve auditability and introduce projections gradually. Be explicit about coexistence, backfill, and dual-write risks.

When should I not use event-store-design?

Skip it if your main need is:

• domain event naming
• business workflow modeling
• message bus integration only
• basic CRUD audit logging
• deciding whether event sourcing is worth the complexity

In those cases, the skill is adjacent but not central.

Is this skill enough to implement a production event store?

Not alone. The skill helps you design the shape of a production-ready solution, but implementation still requires storage-engine specifics, testing, observability, and failure handling. Think of it as design acceleration, not a drop-in subsystem.

How is this different from asking an AI for event sourcing best practices?

The event-store-design skill FAQ answer is simple: scope and structure. Ordinary prompts often return broad best practices. This skill is tuned for event store design decisions such as streams, versions, global position, and append semantics.

How to Improve event-store-design skill

Give sharper constraints, not longer prompts

Better results come from more precise constraints, not more background text. The highest-value details are:

• aggregate count and shape
• contention hotspots
• write throughput
• replay frequency
• latency targets
• retention and compliance requirements

These change the design materially.

Ask for tradeoffs in table form

A good way to improve event-store-design output is to request side-by-side tradeoffs, for example:

• per-stream ordering vs global ordering
• snapshots vs full replay
• single table vs partitioned storage
• database event store vs specialized product

This forces the answer to become decision-oriented rather than descriptive.

Push on failure modes after the first draft

After the first answer, ask follow-up questions like:

• what breaks under duplicate appends
• how consumers recover from partial failures
• what happens during replays while live traffic continues
• how version conflicts are surfaced to writers
• how schema evolution avoids breaking old events

This is often where a decent design becomes implementation-ready.

Provide event examples and command flows

One of the fastest ways to improve the event-store-design usage quality is to include 2 to 5 real event examples and the commands that create them. Concrete examples reveal:

• aggregate boundaries
• event payload size
• metadata needs
• ordering expectations
• idempotency requirements

Even a short sample beats abstract descriptions.

Separate must-haves from preferences

Tell the skill which constraints are hard requirements and which are negotiable. For example:

• must have per-aggregate optimistic concurrency
• must support replayable projections
• prefer PostgreSQL
• prefer simple ops over maximum throughput

That helps avoid designs that are technically elegant but not adoptable by your team.

Watch for these common failure modes

Poor event-store-design for Backend Development output usually shows one of these problems:

• vague stream strategy
• no clear concurrency model
• missing metadata guidance
• no checkpointing plan for consumers
• no replay or snapshot policy
• assumptions that do not match your storage engine

When you see them, ask for a revision anchored to your exact infrastructure.

Improve the skill by narrowing the deliverable

Do not ask for “complete architecture” if you really need one decision. Better prompts are:

• design stream naming and partitioning
• define append contract and version checks
• propose event envelope schema
• choose snapshot rules
• compare storage options for our workload

Narrower requests produce more actionable output.

Validate against real operational scenarios

Before accepting the design, ask the skill to test itself against scenarios such as:

• hot aggregate under concurrent writes
• projector outage and replay catch-up
• tenant growth that changes partition size
• schema change across old and new consumers
• backfill after a bug fix

This quickly exposes weak assumptions.

Use iterative prompts instead of one-shot design

The best way to improve event-store-design skill results is a short loop:

1. get an initial architecture
2. challenge it with load and failure scenarios
3. pin down storage-specific details
4. ask for implementation checklist
5. ask for risks and migration plan

That pattern usually yields a design you can actually build from.