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Spring Boot Dependency Injection

Community
giuseppe-trisciuoglio
spring-boot-dependency-injection

Provides dependency injection patterns for Spring Boot projects, including constructor-first design, optional collaborator handling, bean selection, and wiring validation. Use when creating services and configurations, replacing field injection, or troubleshooting ambiguous or fragile Spring wiring.

Overview

Publishergiuseppe-trisciuoglio
Repositorydeveloper-kit
Skill namespring-boot-dependency-injection
Stars
345
Forks
41
Bundled files
3
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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by giuseppe-trisciuoglio on GitHub. Read the source before you install it.

Installation

Install the Spring Boot Dependency Injection 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-dependency-injection .claude/skills/spring-boot-dependency-injection
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Spring Boot Dependency Injection 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 Dependency Injection 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 Dependency Injection 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 Dependency Injection

Overview

Provides constructor-first dependency injection patterns for Spring Boot:

  • mandatory collaborators via constructor injection
  • optional collaborators via ObjectProvider or no-op fallbacks
  • bean selection via @Primary and @Qualifier
  • validation via minimal context tests before full integration

When to Use

Use this skill when:

  • creating a new @Service, @Component, @Repository, or @Configuration class
  • replacing field injection in legacy Spring code
  • resolving multiple beans of the same type with qualifiers or primary beans
  • handling optional features, adapters, or integrations without null-driven wiring
  • reviewing circular dependencies or brittle context startup failures
  • preparing code for direct constructor-based unit testing

Instructions

1. Separate mandatory and optional collaborators

For each class, identify:

  • mandatory collaborators required for correct behavior
  • optional collaborators that enable integrations, caching, notifications, or feature-flagged behavior

Mandatory collaborators belong in the constructor. Optional ones need an explicit strategy such as ObjectProvider, conditional beans, or a no-op implementation.

2. Default to constructor injection

For application services and adapters:

  • inject mandatory dependencies through the constructor
  • keep injected fields final
  • instantiate the class directly in unit tests without starting Spring

A single constructor is usually enough; @Autowired is unnecessary in that case.

3. Resolve optional behavior intentionally

Good options include:

  • ObjectProvider<T> when lazy access is useful
  • @ConditionalOnProperty or @ConditionalOnMissingBean when wiring should change by configuration
  • a no-op implementation when the caller should not care whether the feature is enabled

Avoid nullable collaborators that leave runtime behavior ambiguous.

4. Use bean selection annotations only when needed

When multiple beans share the same type:

  • use @Primary for the default implementation
  • use @Qualifier for named variants
  • keep the qualifier names stable and easy to grep

If selection rules become complex, move them into a dedicated configuration class instead of spreading them across services.

5. Keep wiring in configuration, not business code

Use @Configuration and @Bean methods when:

  • the object comes from a third-party library
  • conditional creation logic is needed
  • you need environment-specific wiring or explicit composition

Business services should not know how infrastructure collaborators are instantiated.

6. Validate wiring explicitly

After writing a new service or configuration:

  1. Verify the bean loads with a minimal context test:
    java
    @SpringBootTest
    @ContextConfiguration(classes = UserService.class)
    class UserServiceWiringTest {
        @Autowired UserService userService;
        @Test void serviceIsInstantiated() { assertNotNull(userService); }
    }
  2. Run constructor-based unit tests for service behavior (no Spring needed).
  3. Add slice tests only when MVC, JPA, or messaging integration must be verified.
  4. Reserve @SpringBootTest for container-wide wiring validation.

Failures at step 1 indicate wiring issues before business logic is added.

Examples

Example 1: Constructor-first application service

java
@Service
public class UserService {

    private final UserRepository userRepository;
    private final EmailSender emailSender;

    public UserService(UserRepository userRepository, EmailSender emailSender) {
        this.userRepository = userRepository;
        this.emailSender = emailSender;
    }

    public User register(UserRegistrationRequest request) {
        User user = userRepository.save(User.from(request));
        emailSender.sendWelcome(user);
        return user;
    }
}

This class is easy to instantiate directly in a unit test with mocks.

Example 2: Optional dependency with a no-op fallback

java
@Service
public class ReportService {

    private final ReportRepository reportRepository;
    private final NotificationGateway notificationGateway;

    public ReportService(
        ReportRepository reportRepository,
        ObjectProvider<NotificationGateway> notificationGatewayProvider
    ) {
        this.reportRepository = reportRepository;
        this.notificationGateway = notificationGatewayProvider.getIfAvailable(NotificationGateway::noOp);
    }
}

This keeps optional behavior explicit without leaking null handling through the rest of the class.

Example 3: Multiple beans with clear selection

java
@Configuration
public class PaymentConfiguration {

    @Bean
    @Primary
    PaymentGateway stripeGateway() {
        return new StripePaymentGateway();
    }

    @Bean
    @Qualifier("fallbackGateway")
    PaymentGateway mockGateway() {
        return new MockPaymentGateway();
    }
}

Use @Primary for the default path and @Qualifier only where a specific variant is required.

Best Practices

  • Prefer constructor injection for mandatory dependencies.
  • Keep service constructors small; if a class needs too many collaborators, the design probably wants another abstraction.
  • Use no-op or conditional beans instead of nullable optional dependencies.
  • Keep framework-specific creation logic in configuration classes.
  • Test services without Spring first, then add container tests only where they add value.
  • Remove field injection during refactors instead of extending it.

Constraints and Warnings

  • Field injection hides dependencies and makes tests harder to write.
  • Circular dependencies are usually a design problem, not a wiring trick to solve with @Lazy.
  • Overusing qualifiers can make the codebase hard to reason about; prefer better abstractions or clearer configuration.
  • Optional collaborators still need deterministic behavior when absent.
  • Full-context tests can hide the real source of wiring failures if used too early.

References

  • references/reference.md
  • references/examples.md
  • references/spring-official-dependency-injection.md

Related Skills

  • spring-boot-crud-patterns
  • spring-boot-rest-api-standards
  • unit-test-service-layer

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Spring Boot Dependency Injection AI skill do?

Provides dependency injection patterns for Spring Boot projects, including constructor-first design, optional collaborator handling, bean selection, and wiring validation. Use when creating services and configurations, replacing field injection, or troubleshooting ambiguous or fragile Spring wiring.

Why use Spring Boot Dependency Injection on TypingMind?

Because you install it once and use it with any model. Spring Boot Dependency Injection 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 Dependency Injection 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-dependency-injection. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Spring Boot Dependency Injection?

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 Dependency Injection?

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

Is the Spring Boot Dependency Injection 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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