Nw Ddd Event Modeling logo

Nw Ddd Event Modeling

Organization
nWave-ai
nw-ddd-event-modeling

Event Modeling facilitation technique — brainstorm events, identify commands and views, define aggregate boundaries, write Given-When-Then specifications

Overview

PublishernWave-ai
RepositorynWave
Skill namenw-ddd-event-modeling
Stars
616
Forks
65
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by nWave-ai on GitHub. Read the source before you install it.

Installation

Install the Nw Ddd Event Modeling AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-ddd-event-modeling
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nWave-ai/nWave.git /tmp/nWave
mkdir -p .claude/skills
cp -r /tmp/nWave/nWave/skills/nw-ddd-event-modeling .claude/skills/nw-ddd-event-modeling
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nw Ddd Event Modeling in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Nw Ddd Event Modeling on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Nw Ddd Event Modeling is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Event Modeling

Collaborative visual design technique created by Adam Dymitruk. The Event Model IS the specification -- it replaces traditional requirements documents with a single, living visual artifact.

Key Properties

  • Collaborative: Everyone participates (devs, business, UX)
  • Visual: Colored elements on a timeline (physical or digital board)
  • Timeline-based: Events arranged chronologically, left to right
  • Spec-generating: Model directly produces testable Given/When/Then specifications
  • Technology-agnostic: Describes WHAT happens, not HOW it's implemented

The Color System

ColorElementDescriptionExample
OrangeEventSomething that happened (past tense)OrderPlaced, PaymentReceived
BlueCommandUser intent/action (imperative)PlaceOrder, ProcessPayment
GreenRead Model/ViewData displayed to userOrder Summary, Shipping Dashboard
WhiteScreen/UIUser interface wireframeOrder Form, Checkout Page
YellowAutomation/PolicySystem reaction (saga/process manager)"When PaymentReceived, then ConfirmOrder"
RedExternal SystemIntegration pointPayment Gateway, Email Service

Four Phases

Phase 1: Event Brainstorming (10-20 min)

Discover all meaningful things that happen in the system.

Process: Everyone writes events on orange stickies (past tense, domain language) | Place on timeline (left = earlier, right = later) | No filtering -- capture everything | Group related events vertically (these form swimlanes/slices)

Facilitation tips:

  • Start with the happy path -- what happens when everything goes right?
  • Then add error/exception events
  • Ask: "What happens before this? What happens after?"
  • Business people identify events developers miss
  • Don't worry about order precision -- rough chronological is fine

Example timeline:

Timeline ─────────────────────────────────────────────────>

[CustomerRegistered] [ItemAddedToCart] [OrderPlaced] [PaymentReceived]
                     [ItemRemovedFromCart]            [PaymentFailed]
                                       [OrderCancelled] [OrderConfirmed]
                                                        [ItemShipped]
                                                        [RefundRequested]

Phase 2: Commands and Views (15-25 min)

Understand what triggers events and what users need to see.

Commands (blue): What action causes each event? Who initiates it? Place ABOVE events.

Read Models (green): What information does the user need to act? What does the screen show after? Place BELOW events.

Screens (white): What does the UI look like? Sketch wireframes. Place at top.

Wiring pattern:

Screen -> Command -> Event(s) -> Read Model -> Screen

Phase 3: Automations and Integrations (10-15 min)

Find system-driven reactions to events.

Automations (yellow): "When [event] happens, the system should [command]." These become sagas or process managers. Place between triggering event and resulting command.

External systems (red): Payment gateways, email services, shipping providers. Integration boundaries.

Phase 4: Given/When/Then Specifications (10-20 min)

Turn the model into precise, testable specifications.

For each command-event combination:

GIVEN:
  - CustomerRegistered { customerId: "C1", name: "Ale" }
  - ItemAddedToCart { cartId: "CART1", itemId: "ITEM1", quantity: 2 }

WHEN:
  - PlaceOrder { cartId: "CART1", customerId: "C1" }

THEN:
  - OrderPlaced { orderId: "O1", customerId: "C1", items: [...], total: 59.98 }

These specifications become: Tests (directly translatable) | Documentation (readable by everyone) | Contract (unambiguous business-dev agreement)

Four Information Flow Patterns

The Event Model reveals four patterns:

1. Command (State Change): Screen -> Command -> Event(s). User action changes state. Implementation: command handler validates, aggregate emits events.

2. View (Information Retrieval): Event(s) -> Projection -> Read Model -> Screen. Events transformed into query-optimized views. Implementation: projection subscribes and updates read model.

3. Automation (System Reaction): Event(s) -> Policy/Saga -> Command. System reacts to events by issuing new commands. Implementation: saga/process manager.

4. Translation (External Integration): External Event -> Translator -> Internal Command (or reverse). Boundary between systems. Implementation: anti-corruption layer.

From Model to Vertical Slices

Each column in the Event Model (Screen -> Command -> Event -> Read Model) becomes a vertical slice -- an independently implementable feature.

           Slice 1         Slice 2         Slice 3
         ┌──────────┐   ┌──────────┐   ┌──────────┐
UI       │ OrderForm │   │ PaymentPg│   │ Dashboard │
         ├──────────┤   ├──────────┤   ├──────────┤
Cmd/Qry  │PlaceOrder │   │ProcessPay│   │GetOrders  │
         ├──────────┤   ├──────────┤   ├──────────┤
Domain   │OrderAgg   │   │PaymentAgg│   │OrderProj  │
         ├──────────┤   ├──────────┤   ├──────────┤
Infra    │EventStore │   │EventStore│   │ReadModelDB│
         └──────────┘   └──────────┘   └──────────┘

Benefits: Each slice independently implementable and deployable | Easy to parallelize across team | Model shows exactly how many slices exist and their dependencies | Each slice maps to a portion of the Event Model

Specification Patterns

Happy path: GIVEN events that set up valid state | WHEN valid command | THEN expected events

Validation failure: GIVEN events (possibly none) | WHEN invalid command | THEN error (no events emitted)

Idempotency: GIVEN events including effect already applied | WHEN same command again | THEN no new events

State-dependent: Same command produces different results depending on prior events

Event Modeling vs Other Techniques

AspectEvent ModelingEventStormingDDD Strategic Design
FocusComplete system designDomain explorationBounded context mapping
OutputFull spec + implementation slicesShared understandingContext map + language
DetailVery detailed (down to fields)Medium (event+command level)High-level (boundaries)
DurationHalf day to full dayHours to daysOngoing
Code generationDirectly possibleNot directlyNot directly
TestingProduces testable specsProduces insightsProduces guidance

These techniques are complementary: EventStorming to explore/understand | DDD Strategic Design to identify contexts | Event Modeling to design implementation within each context.

Session Facilitation Guide

Preparation: Invite developers + product owner + domain experts + UX designer | Duration: 2-4 hours (new system), 1-2 hours (feature) | Tools: Miro (digital) or large wall with colored stickies | Pre-work: brief domain introduction (2-3 sentences)

Flow: Intro (5 min): explain colors and phases | Event brainstorm (15 min): everyone writes, place on timeline | Organize (10 min): cluster, de-duplicate, identify gaps | Commands & Views (20 min): blue and green stickies | Wire it up (10 min): draw arrows showing data flow | Automations (10 min): policies and external systems | Given/When/Then (20 min): specs for key slices | Review (10 min): walk through entire model as narrative

Common mistakes: Too many events at once (start with happy path) | Technical events instead of business language | Skipping views (read models as important as commands) | Not involving business people | Jumping to implementation before finishing model

Frequently asked questions

What does the Nw Ddd Event Modeling AI skill do?

Event Modeling facilitation technique — brainstorm events, identify commands and views, define aggregate boundaries, write Given-When-Then specifications

Why use Nw Ddd Event Modeling on TypingMind?

Because you install it once and use it with any model. Nw Ddd Event Modeling is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Nw Ddd Event Modeling in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-ddd-event-modeling. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Nw Ddd Event Modeling?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Nw Ddd Event Modeling?

As many as you like. As long as a model supports skills, you can use Nw Ddd Event Modeling with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Nw Ddd Event Modeling AI skill free?

Yes. It is published on GitHub by nWave-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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