Ddd Aggregate logo

Ddd Aggregate

CommunityPopular
ruvnet
ddd-aggregate

Scaffold an aggregate root with entity, value objects, repository interface, domain events, and test stubs. Use when adding a new aggregate to an existing bounded context, modeling a new business concept that owns invariants, or generating the boilerplate for an entity + repo + events triplet.

Overview

Publisherruvnet
Repositoryruflo
Skill nameddd-aggregate
Stars
72.7K
Forks
8.6K
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 ruvnet on GitHub. Read the source before you install it.

Installation

Install the Ddd Aggregate 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.
  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/ruvnet/ruflo.git /tmp/ruflo
mkdir -p .claude/skills
cp -r /tmp/ruflo/plugins/ruflo-ddd/skills/ddd-aggregate .claude/skills/ddd-aggregate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ddd Aggregate 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 Ddd Aggregate 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 Ddd Aggregate 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.

Scaffold a complete aggregate root inside a bounded context.

Parse $ARGUMENTS as <context-name> <aggregate-name> (both kebab-case). The context must already exist under src/.

Steps

  1. Validate: Confirm src/<context>/domain/ exists. If not, suggest running /ddd-context <context> first.

  2. Pre-task hook: npx @claude-flow/cli@latest hooks pre-task --description "DDD aggregate: <aggregate-name> in <context>"

  3. Create aggregate root entity:

    • File: src/<context>/domain/entities/<aggregate-name>.entity.ts
    • Include: unique ID field, constructor with invariant validation, domain methods that enforce business rules, equals() based on identity
    • Export a TypeScript class extending or implementing a base AggregateRoot interface
  4. Create value objects:

    • File: src/<context>/domain/value-objects/<aggregate-name>-id.value-object.ts
    • Include: immutable ID value object with factory method and validation
    • Add additional value objects as properties of the aggregate suggest them
  5. Create repository interface:

    • File: src/<context>/domain/repositories/<aggregate-name>.repository.ts
    • Include: findById, save, delete methods
    • Use the aggregate root and its ID value object as types
    • This is an interface only -- no implementation (infrastructure concern)
  6. Create domain events:

    • File: src/<context>/domain/events/<aggregate-name>-created.event.ts
    • File: src/<context>/domain/events/<aggregate-name>-updated.event.ts
    • Include: event name (past tense), timestamp, aggregate ID, payload
  7. Create unit test stubs:

    • File: src/<context>/domain/entities/<aggregate-name>.entity.test.ts
    • Include: test cases for construction invariants, domain methods, equality
    • Use describe/it with should [behavior] when [condition] names
  8. Update barrel exports: Add new files to the relevant index.ts barrel files.

  9. Store in domain model graph:

    mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-store --parent "context:<context>" --child "aggregate:<aggregate-name>" --relation "contains"
    mcp__plugin_ruflo-core_ruflo__memory_store --key "ddd-aggregate-<context>-<aggregate-name>" --value "AGGREGATE_SUMMARY" --namespace tasks
  10. Post-task hook: npx @claude-flow/cli@latest hooks post-task --task-id "ddd-aggregate-<aggregate-name>" --success true --train-neural true

Frequently asked questions

What does the Ddd Aggregate AI skill do?

Scaffold an aggregate root with entity, value objects, repository interface, domain events, and test stubs. Use when adding a new aggregate to an existing bounded context, modeling a new business concept that owns invariants, or generating the boilerplate for an entity + repo + events triplet.

Why use Ddd Aggregate on TypingMind?

Because you install it once and use it with any model. Ddd Aggregate 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 Ddd Aggregate in TypingMind?

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

Which AI models can use Ddd Aggregate?

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 Ddd Aggregate?

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

Is the Ddd Aggregate AI skill free?

Yes. It is published on GitHub by ruvnet 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇