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Golang Dependency Injection

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samber
golang-dependency-injection

Comprehensive guide for dependency injection (DI) in Golang. Covers why DI matters (testability, loose coupling, separation of concerns, lifecycle management), manual constructor injection, and DI library comparison (google/wire, uber-go/dig, uber-go/fx, samber/do). Use this skill when designing service architecture, setting up dependency injection, refactoring tightly coupled code, managing singletons or service factories, or when the user asks about inversion of control, service containers, or wiring dependencies in Go. For a specific DI library, → See `samber/cc-skills-golang@golang-google-wire`, `samber/cc-skills-golang@golang-uber-dig`, `samber/cc-skills-golang@golang-uber-fx`, or `samber/cc-skills-golang@golang-samber-do` skills.

Overview

Publishersamber
Repositorycc-skills-golang
Skill namegolang-dependency-injection
Stars
3.3K
Forks
213
Bundled files
5
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.

  • 5 bundled files

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

  • Open source

    Published by samber on GitHub. Read the source before you install it.

Installation

Install the Golang 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/samber/cc-skills-golang.git /tmp/cc-skills-golang
mkdir -p .claude/skills
cp -r /tmp/cc-skills-golang/skills/golang-dependency-injection .claude/skills/golang-dependency-injection
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Golang 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 Golang 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 Golang 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.

Persona: You are a Go software architect. You guide teams toward testable, loosely coupled designs — you choose the simplest DI approach that solves the problem, and you never over-engineer.

Orchestration mode: Fan out the three sub-agents described in Refactor mode (global/init discovery, concrete-dependency mapping, service-locator detection) when refactoring a large coupled codebase toward dependency injection, and consolidate into one migration plan. On Claude Code, use ultracode to opt into multi-agent orchestration explicitly.

Modes:

  • Design mode (new project, new service, or adding a service to an existing DI setup): assess the existing dependency graph and lifecycle needs; recommend manual injection or a library from the decision table; then generate the wiring code.
  • Refactor mode (existing coupled code): use up to 3 parallel sub-agents — Agent 1 identifies global variables and init() service setup, Agent 2 maps concrete type dependencies that should become interfaces, Agent 3 locates service-locator anti-patterns (container passed as argument) — then consolidate findings and propose a migration plan.

Community default. A company skill that explicitly supersedes samber/cc-skills-golang@golang-dependency-injection skill takes precedence.

Dependency Injection in Go

Dependency injection (DI) means passing dependencies to a component rather than having it create or find them. In Go, this is how you build testable, loosely coupled applications — your services declare what they need, and the caller (or container) provides it.

This skill is not exhaustive. When using a DI library (google/wire, uber-go/dig, uber-go/fx, samber/do), refer to the library's official documentation and code examples for current API signatures.

For interface-based design foundations (accept interfaces, return structs), see the samber/cc-skills-golang@golang-structs-interfaces skill.

Best Practices Summary

  1. Dependencies MUST be injected via constructors — NEVER use global variables or init() for service setup
  2. Small projects (< 10 services) SHOULD use manual constructor injection — no library needed
  3. Interfaces MUST be defined where consumed, not where implemented — accept interfaces, return structs
  4. NEVER use global registries or package-level service locators
  5. The DI container MUST only exist at the composition root (main() or app startup) — NEVER pass the container as a dependency
  6. Prefer lazy initialization — only create services when first requested
  7. Use singletons for stateful services (DB connections, caches) and transients for stateless ones
  8. Mock at the interface boundary — DI makes this trivial
  9. Keep the dependency graph shallow — deep chains signal design problems
  10. Choose the right DI library for your project size and team — see the decision table below

Why Dependency Injection?

Problem without DIHow DI solves it
Functions create their own dependenciesDependencies are injected — swap implementations freely
Testing requires real databases, APIsPass mock implementations in tests
Changing one component breaks othersLoose coupling via interfaces — components don't know each other's internals
Services initialized everywhereCentralized container manages lifecycle (singleton, factory, lazy)
All services loaded at startupLazy loading — services created only when first requested
Global state and init() functionsExplicit wiring at startup — predictable, debuggable

DI shines in applications with many interconnected services — HTTP servers, microservices, CLI tools with plugins. For a small script with 2-3 functions, manual wiring is fine. Don't over-engineer.

Manual Constructor Injection (No Library)

For small projects, pass dependencies through constructors. See Manual DI examples for a complete application example.

go
// ✓ Good — explicit dependencies, testable
type UserService struct {
    db     UserStore
    mailer Mailer
    logger *slog.Logger
}

func NewUserService(db UserStore, mailer Mailer, logger *slog.Logger) *UserService {
    return &UserService{db: db, mailer: mailer, logger: logger}
}

// main.go — manual wiring
func main() {
    logger := slog.Default()
    db := postgres.NewUserStore(connStr)
    mailer := smtp.NewMailer(smtpAddr)
    userSvc := NewUserService(db, mailer, logger)
    orderSvc := NewOrderService(db, logger)
    api := NewAPI(userSvc, orderSvc, logger)
    api.ListenAndServe(":8080")
}
go
// ✗ Bad — hardcoded dependencies, untestable
type UserService struct {
    db *sql.DB
}

func NewUserService() *UserService {
    db, _ := sql.Open("postgres", os.Getenv("DATABASE_URL")) // hidden dependency
    return &UserService{db: db}
}

Manual DI breaks down when:

  • You have 15+ services with cross-dependencies
  • You need lifecycle management (health checks, graceful shutdown)
  • You want lazy initialization or scoped containers
  • Wiring order becomes fragile and hard to maintain

DI Library Comparison

Go has three main approaches to DI libraries:

Decision Table

CriteriaManualgoogle/wireuber-go/dig + fxsamber/do
Project sizeSmall (< 10 services)Medium-LargeLargeAny size
Type safetyCompile-timeCompile-time (codegen)Runtime (reflection)Compile-time (generics)
Code generationNoneRequired (wire_gen.go)NoneNone
ReflectionNoneNoneYesNone
API styleN/AProvider sets + build tagsStruct tags + decoratorsSimple, generic functions
Lazy loadingManualN/A (all eager)Built-in (fx)Built-in
SingletonsManualBuilt-inBuilt-inBuilt-in
Transient/factoryManualManualBuilt-inBuilt-in
Scopes/modulesManualProvider setsModule system (fx)Built-in (hierarchical)
Health checksManualManualManualBuilt-in interface
Graceful shutdownManualManualBuilt-in (fx)Built-in interface
Container cloningN/AN/AN/ABuilt-in
DebuggingPrint statementsCompile errorsfx.Visualize()ExplainInjector(), web interface
Go versionAnyAnyAny1.18+ (generics)
Learning curveNoneMediumHighLow

Quick Comparison: Wiring Style

The same graph — Config -> Database -> UserStore -> UserService -> API — wired by hand and by a container. The contrast is what the wiring code encodes: an ordered call sequence you maintain, versus a set of providers the container orders for you.

go
// Manual — you own the order; adding a dependency means editing every call site downstream
cfg := NewConfig()
db := NewDatabase(cfg)
store := NewUserStore(db)
svc := NewUserService(store)
api := NewAPI(svc)
api.Run()
// No shutdown hooks, health checks, or lazy loading — add them yourself

// Container (samber/do) — order is derived from the constructor signatures
i := do.New()
do.Provide(i, NewConfig)
do.Provide(i, NewDatabase)
do.Provide(i, NewUserStore)
do.Provide(i, NewUserService)
api := do.MustInvoke[*API](i)
api.Run()
defer i.Shutdown() // shutdown and health checks come from the container

google/wire and uber-go/fx express the same graph differently: wire generates the manual sequence above at build time from a wire.Build provider list (cleanup via func() returned by providers, no lifecycle hooks), while fx registers providers with fx.Provide and resolves them by reflection at runtime with OnStart/OnStop hooks. Full wiring examples for each: google/wire, uber-go/dig + fx, samber/do.

Testing with DI

DI makes testing straightforward — inject mocks instead of real implementations:

go
// Define a mock
type MockUserStore struct {
    users map[string]*User
}

func (m *MockUserStore) FindByID(ctx context.Context, id string) (*User, error) {
    u, ok := m.users[id]
    if !ok {
        return nil, ErrNotFound
    }
    return u, nil
}

// Test with manual injection
func TestUserService_GetUser(t *testing.T) {
    mock := &MockUserStore{
        users: map[string]*User{"1": {ID: "1", Name: "Alice"}},
    }
    svc := NewUserService(mock, nil, slog.Default())

    user, err := svc.GetUser(context.Background(), "1")
    if err != nil {
        t.Fatalf("unexpected error: %v", err)
    }
    if user.Name != "Alice" {
        t.Errorf("got %q, want %q", user.Name, "Alice")
    }
}

Testing with samber/do — Clone and Override

Container cloning creates an isolated copy where you override only the services you need to mock:

go
func TestUserService_WithDo(t *testing.T) {
    // Create a test injector with mock implementation
    testInjector := do.New()

    // Provide the mock UserStore interface
    do.OverrideValue[UserStore](testInjector, &MockUserStore{
        users: map[string]*User{"1": {ID: "1", Name: "Alice"}},
    })

    // Provide other real services as needed
    do.Provide[*slog.Logger](testInjector, func(i *do.Injector) (*slog.Logger, error) {
        return slog.Default(), nil
    })

    svc := do.MustInvoke[*UserService](testInjector)
    user, err := svc.GetUser(context.Background(), "1")
    // ... assertions
}

This is particularly useful for integration tests where you want most services to be real but need to mock a specific boundary (database, external API, mailer).

When to Adopt a DI Library

SignalAction
< 10 services, simple dependenciesStay with manual constructor injection
10-20 services, some cross-cutting concernsConsider a DI library
20+ services, lifecycle management neededStrongly recommended
Need health checks, graceful shutdownUse a library with built-in lifecycle support
Team unfamiliar with DI conceptsStart manual, migrate incrementally

Common Mistakes

MistakeFix
Global variables as dependenciesPass through constructors or DI container
init() for service setupExplicit initialization in main() or container
Depending on concrete typesAccept interfaces at consumption boundaries
Passing the container everywhere (service locator)Inject specific dependencies, not the container
Deep dependency chains (A->B->C->D->E)Flatten — most services should depend on repositories and config directly
Creating a new container per requestOne container per application; use scopes for request-level isolation

Cross-References

  • → See samber/cc-skills-golang@golang-samber-do skill for detailed samber/do usage patterns
  • → See samber/cc-skills-golang@golang-structs-interfaces skill for interface design and composition
  • → See samber/cc-skills-golang@golang-testing skill for testing with dependency injection
  • → See samber/cc-skills-golang@golang-project-layout skill for DI initialization placement

References

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 Golang Dependency Injection AI skill do?

Comprehensive guide for dependency injection (DI) in Golang. Covers why DI matters (testability, loose coupling, separation of concerns, lifecycle management), manual constructor injection, and DI library comparison (google/wire, uber-go/dig, uber-go/fx, samber/do). Use this skill when designing service architecture, setting up dependency injection, refactoring tightly coupled code, managing singletons or service factories, or when the user asks about inversion of control, service containers, or wiring dependencies in Go. For a specific DI library, → See `samber/cc-skills-golang@golang-goog...

Why use Golang Dependency Injection on TypingMind?

Because you install it once and use it with any model. Golang 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 Golang Dependency Injection in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/samber/cc-skills-golang/tree/main/skills/golang-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 Golang 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 Golang Dependency Injection?

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

Is the Golang Dependency Injection AI skill free?

Yes. It is published on GitHub by samber 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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