Spring Boot Project Creator logo

Spring Boot Project Creator

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giuseppe-trisciuoglio
spring-boot-project-creator

Creates and scaffolds a new Spring Boot project (3.x or 4.x) by downloading from Spring Initializr, generating package structure (DDD or Layered architecture), configuring JPA, SpringDoc OpenAPI, and Docker Compose services (PostgreSQL, Redis, MongoDB). Use when creating a new Java Spring Boot project from scratch, bootstrapping a microservice, or initializing a backend application.

Overview

Publishergiuseppe-trisciuoglio
Repositorydeveloper-kit
Skill namespring-boot-project-creator
Stars
345
Forks
41
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 giuseppe-trisciuoglio on GitHub. Read the source before you install it.

Installation

Install the Spring Boot Project Creator 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/giuseppe-trisciuoglio/developer-kit.git /tmp/developer-kit
mkdir -p .claude/skills
cp -r /tmp/developer-kit/plugins/developer-kit-java/skills/spring-boot-project-creator .claude/skills/spring-boot-project-creator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Spring Boot Project Creator 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 Spring Boot Project Creator 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 Spring Boot Project Creator 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.

Spring Boot Project Creator

Overview

Generates a fully configured Spring Boot project from scratch using the Spring Initializr API. The skill walks the user through selecting project parameters, choosing an architecture style (DDD or Layered), configuring data stores, and setting up Docker Compose for local development. The result is a build-ready project with standardized structure, dependency management, and configuration.

When to Use

  • Bootstrap a new Spring Boot 3.x or 4.x project with a standard structure.
  • Initialize a backend microservice with JPA, SpringDoc OpenAPI, and Docker Compose.
  • Scaffold a project following either DDD (Domain-Driven Design) or Layered (Controller/Service/Repository/Model) architecture.
  • Set up local development infrastructure with PostgreSQL, Redis, and/or MongoDB via Docker Compose.
  • Trigger phrases: "create spring boot project", "new spring boot app", "bootstrap java project", "scaffold spring boot microservice", "initialize spring boot backend", "generate spring boot project".

Prerequisites

Before starting, ensure the following tools are installed:

  • Java Development Kit (JDK): Version 17+ (Java 21 recommended for Spring Boot 3.x/4.x)
  • Apache Maven: Build tool (Spring Initializr generates Maven projects by default)
  • Docker and Docker Compose: For running local infrastructure services
  • curl and unzip: For downloading and extracting the project from Spring Initializr

Instructions

Follow these steps to create a new Spring Boot project.

1. Gather Project Configuration

Ask the user for the following project parameters using AskUserQuestion. Provide sensible defaults:

ParameterDefaultOptions
Group IDcom.exampleAny valid Java package name
Artifact IDdemoKebab-case identifier
Package NameSame as Group IDValid Java package
Spring Boot Version3.4.53.4.x, 4.0.x (check start.spring.io for latest)
Java Version2117, 21
ArchitectureUser choiceDDD or Layered
Docker ServicesUser choicePostgreSQL, Redis, MongoDB (multi-select)
Build Toolmavenmaven, gradle

2. Generate Project with Spring Initializr

Use curl to download the project scaffold from start.spring.io.

Base dependencies (always included):

  • web — Spring Web MVC
  • validation — Jakarta Bean Validation
  • data-jpa — Spring Data JPA
  • testcontainers — Testcontainers support

Conditional dependencies (based on Docker Services selection):

  • PostgreSQL selected → add postgresql
  • Redis selected → add data-redis
  • MongoDB selected → add data-mongodb
bash
# Example for Spring Boot 3.4.5 with PostgreSQL only
curl -s https://start.spring.io/starter.zip \
  -d type=maven-project \
  -d language=java \
  -d bootVersion=3.4.5 \
  -d groupId=com.example \
  -d artifactId=demo \
  -d packageName=com.example \
  -d javaVersion=21 \
  -d packaging=jar \
  -d dependencies=web,data-jpa,postgresql,validation,testcontainers \
  -o starter.zip

unzip -o starter.zip -d ./demo
rm starter.zip
cd demo

3. Add Additional Dependencies

Edit pom.xml to add SpringDoc OpenAPI and ArchUnit for architectural testing.

xml
<!-- SpringDoc OpenAPI -->
<dependency>
    <groupId>org.springdoc</groupId>
    <artifactId>springdoc-openapi-starter-webmvc-ui</artifactId>
    <version>2.8.15</version>
</dependency>

<!-- ArchUnit for architecture tests -->
<dependency>
    <groupId>com.tngtech.archunit</groupId>
    <artifactId>archunit-junit5</artifactId>
    <version>1.4.1</version>
    <scope>test</scope>
</dependency>

4. Create Architecture Structure

Based on the user's choice, create the package structure under src/main/java/<packagePath>/.

Option A: Layered Architecture
src/main/java/com/example/
├── controller/        # REST controllers (@RestController)
├── service/           # Business logic (@Service)
├── repository/        # Data access (@Repository, Spring Data interfaces)
├── model/             # JPA entities (@Entity)
│   └── dto/           # Request/Response DTOs (Java records)
├── config/            # Configuration classes (@Configuration)
└── exception/         # Custom exceptions and @ControllerAdvice

Create placeholder classes for each layer:

  • config/OpenApiConfig.java — SpringDoc OpenAPI configuration bean
  • exception/GlobalExceptionHandler.java@RestControllerAdvice with standard error handling
  • model/dto/ErrorResponse.java — Standard error response record
Option B: DDD (Domain-Driven Design) Architecture
src/main/java/com/example/
├── domain/                 # Core domain (framework-free)
│   ├── model/              # Entities, Value Objects, Aggregates
│   ├── repository/         # Repository interfaces (ports)
│   └── exception/          # Domain exceptions
├── application/            # Use cases / Application services
│   ├── service/            # @Service orchestration
│   └── dto/                # Input/Output DTOs (records)
├── infrastructure/         # External adapters
│   ├── persistence/        # JPA entities, Spring Data repos
│   └── config/             # Spring @Configuration
└── presentation/           # REST API layer
    ├── controller/         # @RestController
    └── exception/          # @RestControllerAdvice

Create placeholder classes for each layer:

  • infrastructure/config/OpenApiConfig.java — SpringDoc OpenAPI configuration bean
  • presentation/exception/GlobalExceptionHandler.java@RestControllerAdvice with standard error handling
  • application/dto/ErrorResponse.java — Standard error response record

5. Configure Application Properties

Create src/main/resources/application.properties with the selected services.

Always include:

properties
# Application
spring.application.name=${artifactId}

# SpringDoc OpenAPI
springdoc.swagger-ui.doc-expansion=none
springdoc.swagger-ui.operations-sorter=alpha
springdoc.swagger-ui.tags-sorter=alpha

If PostgreSQL is selected:

properties
# PostgreSQL / JPA
spring.datasource.driver-class-name=org.postgresql.Driver
spring.datasource.url=jdbc:postgresql://localhost:5432/${POSTGRES_DB:postgres}
spring.datasource.username=${POSTGRES_USER:postgres}
spring.datasource.password=${POSTGRES_PASSWORD:changeme}
spring.jpa.hibernate.ddl-auto=update
spring.jpa.show-sql=true
spring.jpa.properties.hibernate.format_sql=true

If Redis is selected:

properties
# Redis
spring.data.redis.host=localhost
spring.data.redis.port=6379
spring.data.redis.password=${REDIS_PASSWORD:changeme}

If MongoDB is selected:

properties
# MongoDB
spring.data.mongodb.host=localhost
spring.data.mongodb.port=27017
spring.data.mongodb.authentication-database=admin
spring.data.mongodb.username=${MONGO_USER:root}
spring.data.mongodb.password=${MONGO_PASSWORD:changeme}
spring.data.mongodb.database=${MONGO_DB:test}

6. Set Up Docker Compose

Create docker-compose.yaml at the project root with only the services the user selected.

yaml
services:
  # Include if PostgreSQL selected
  postgresql:
    image: postgres:17
    ports:
      - "5432:5432"
    environment:
      POSTGRES_USER: ${POSTGRES_USER:-postgres}
      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-changeme}
      POSTGRES_DB: ${POSTGRES_DB:-postgres}
    volumes:
      - ./postgres_data:/var/lib/postgresql/data

  # Include if Redis selected
  redis:
    image: redis:7
    ports:
      - "6379:6379"
    command: redis-server --requirepass ${REDIS_PASSWORD:-changeme}
    volumes:
      - ./redis_data:/data

  # Include if MongoDB selected
  mongodb:
    image: mongo:8
    ports:
      - "27017:27017"
    environment:
      MONGO_INITDB_ROOT_USERNAME: ${MONGO_USER:-root}
      MONGO_INITDB_ROOT_PASSWORD: ${MONGO_PASSWORD:-changeme}
    volumes:
      - ./mongo_data:/data/db

7. Create .env File for Docker Compose

Create a .env file at the project root with default credentials for local development:

env
# PostgreSQL
POSTGRES_USER=postgres
POSTGRES_PASSWORD=changeme
POSTGRES_DB=postgres

# Redis
REDIS_PASSWORD=changeme

# MongoDB
MONGO_USER=root
MONGO_PASSWORD=changeme
MONGO_DB=test

Include only the variables for the services the user selected. Docker Compose automatically loads this file.

8. Update .gitignore

Append Docker Compose volume directories and the .env file to .gitignore:

# Docker Compose
.env
postgres_data/
redis_data/
mongo_data/

9. Verify the Build

Run the Maven build to confirm the project compiles and tests pass:

bash
./mvnw clean verify

If the build succeeds, inform the user. If it fails, diagnose and fix the issue before proceeding.

10. Present Summary to User

Display a summary of the created project:

Project Created Successfully

  Artifact:      <artifactId>
  Spring Boot:   <version>
  Java:          <javaVersion>
  Architecture:  <DDD | Layered>
  Build Tool:    Maven
  Docker:        <services list>

  Directory:     ./<artifactId>/

  Next Steps:
    1. cd <artifactId>
    2. docker compose up -d
    3. ./mvnw spring-boot:run
    4. Open http://localhost:8080/swagger-ui.html

Architecture Patterns

Layered Architecture

Traditional three-tier architecture with clear separation of concerns:

LayerPackageResponsibility
Presentationcontroller/HTTP endpoints, request/response mapping
Businessservice/Business logic, transaction management
Data Accessrepository/Database operations via Spring Data
Domainmodel/JPA entities and DTOs

Best for: Simple CRUD applications, small-to-medium services, teams new to Spring Boot.

DDD Architecture

Domain-Driven Design with hexagonal boundaries:

LayerPackageResponsibility
Domaindomain/Entities, value objects, domain services (framework-free)
Applicationapplication/Use cases, orchestration, DTO mapping
Infrastructureinfrastructure/JPA adapters, external integrations, configuration
Presentationpresentation/REST controllers, error handling

Best for: Complex business domains, microservices with rich logic, long-lived projects.

Examples

Example 1: Simple REST API with PostgreSQL (Layered)

User request: "Create a Spring Boot project for a REST API with PostgreSQL"

bash
curl -s https://start.spring.io/starter.zip \
  -d type=maven-project \
  -d bootVersion=3.4.5 \
  -d groupId=com.example \
  -d artifactId=my-api \
  -d packageName=com.example.myapi \
  -d javaVersion=21 \
  -d dependencies=web,data-jpa,postgresql,validation,testcontainers \
  -o starter.zip

Result: Layered project with controller/, service/, repository/, model/ packages, PostgreSQL Docker Compose, and SpringDoc OpenAPI.

Example 2: Microservice with DDD and Multiple Stores

User request: "Bootstrap a Spring Boot 3 microservice with DDD, PostgreSQL and Redis"

bash
curl -s https://start.spring.io/starter.zip \
  -d type=maven-project \
  -d bootVersion=3.4.5 \
  -d groupId=com.acme \
  -d artifactId=order-service \
  -d packageName=com.acme.order \
  -d javaVersion=21 \
  -d dependencies=web,data-jpa,postgresql,data-redis,validation,testcontainers \
  -o starter.zip

Result: DDD project with domain/, application/, infrastructure/, presentation/ packages, PostgreSQL + Redis Docker Compose, and SpringDoc OpenAPI.

Best Practices

  • Always use Spring Initializr for project generation to get the correct dependency management and parent POM.
  • Use Java records for DTOs — they are immutable and concise.
  • Keep domain layer framework-free in DDD architecture — no Spring annotations in domain/.
  • Use environment variables for sensitive configuration in production (database passwords, etc.).
  • Pin Docker image versions in docker-compose.yaml to avoid unexpected breaking changes.
  • Run ./mvnw clean verify after setup to ensure everything compiles and tests pass.
  • Add Testcontainers for integration tests instead of relying on Docker Compose.

Constraints and Warnings

  • Spring Initializr requires internet access — this skill cannot work offline.
  • Spring Boot 4.x availability depends on the current release cycle — check start.spring.io for latest versions.
  • Docker Compose credentials are loaded from .env file (git-ignored) — never commit secrets to version control.
  • The spring.jpa.hibernate.ddl-auto=update setting is for development only — use Flyway or Liquibase in production.
  • ArchUnit version must be compatible with the JUnit 5 version bundled with Spring Boot.

Frequently asked questions

What does the Spring Boot Project Creator AI skill do?

Creates and scaffolds a new Spring Boot project (3.x or 4.x) by downloading from Spring Initializr, generating package structure (DDD or Layered architecture), configuring JPA, SpringDoc OpenAPI, and Docker Compose services (PostgreSQL, Redis, MongoDB). Use when creating a new Java Spring Boot project from scratch, bootstrapping a microservice, or initializing a backend application.

Why use Spring Boot Project Creator on TypingMind?

Because you install it once and use it with any model. Spring Boot Project Creator 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 Spring Boot Project Creator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/spring-boot-project-creator. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Spring Boot Project Creator?

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 Spring Boot Project Creator?

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

Is the Spring Boot Project Creator AI skill free?

Yes. It is published on GitHub by giuseppe-trisciuoglio 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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