golang-dependency-injection▌
samber/cc-skills-golang · updated Apr 8, 2026
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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.
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.
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-injectionskill 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
- Dependencies MUST be injected via constructors — NEVER use global variables or
init()for service setup - Small projects (< 10 services) SHOULD use manual constructor injection — no library needed
- Interfaces MUST be defined where consumed, not where implemented — accept interfaces, return structs
- NEVER use global registries or package-level service locators
- The DI container MUST only exist at the composition root (
main()or app startup) — NEVER pass the container as a dependency - Prefer lazy initialization — only create services when first requested
- Use singletons for stateful services (DB connections, caches) and transients for stateless ones
- Mock at the interface boundary — DI makes this trivial
- Keep the dependency graph shallow — deep chains signal design problems
- Choose the right DI library for your project size and team — see the decision table below
Why Dependency Injection?
| Problem without DI | How DI solves it |
|---|---|
| Functions create their own dependencies | Dependencies are injected — swap implementations freely |
| Testing requires real databases, APIs | Pass mock implementations in tests |
| Changing one component breaks others | Loose coupling via interfaces — components don't know each other's internals |
| Services initialized everywhere | Centralized container manages lifecycle (singleton, factory, lazy) |
| All services loaded at startup | Lazy loading — services created only when first requested |
Global state and init() functions |
Explicit 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.
// ✓ 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")
}
// ✗ 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:
- google/wire examples — Compile-time code generation
- uber-go/dig + fx examples — Reflection-based framework
- samber/do examples — Generics-based, no code generation
Decision Table
| Criteria | Manual | google/wire | uber-go/dig + fx | samber/do |
|---|---|---|---|---|
| Project size | Small (< 10 services) | Medium-Large | Large | Any size |
| Type safety | Compile-time | Compile-time (codegen) | Runtime (reflection) | Compile-time (generics) |
| Code generation | None | Required (wire_gen.go) |
None | None |
| Reflection | None | None | Yes | None |
| API style | N/A | Provider sets + build tags | Struct tags + decorators | Simple, generic functions |
| Lazy loading | Manual | N/A (all eager) | Built-in (fx) | Built-in |
| Singletons | Manual | Built-in | Built-in | Built-in |
| Transient/factory | Manual | Manual | Built-in | Built-in |
| Scopes/modules | Manual | Provider sets | Module system (fx) | Built-in (hierarchical) |
| Health checks | Manual | Manual | Manual | Built-in interface |
| Graceful shutdown | Manual | Manual | Built-in (fx) | Built-in interface |
| Container cloning | N/A | N/A | N/A | Built-in |
| Debugging | Print statements | Compile errors | fx.Visualize() |
ExplainInjector(), web interface |
| Go version | Any | Any | Any | 1.18+ (generics) |
| Learning curve | None | Medium | High | Low |
Quick Comparison: Same App, Four Ways
The dependency graph: Config -> Database -> UserStore -> UserService -> API
Manual:
cfg := NewConfig()
db := NewDatabase(cfg)
store := NewUserStore(db)
svc := NewUserService(store)
api := NewAPI(svc)
api.Run()
// No automatic shutdown, health checks, or lazy loading
google/wire:
// wire.go — then run: wire ./...
func InitializeAPI() (*API, error) {
wire.Build(NewConfig, NewDatabase, NewUserStore, NewUserService, NewAPI)
return nil, nil
}
// No shutdown or health check support
uber-go/fx:
app := fx.New(
fx.Provide(NewConfig, NewDatabase, NewUserStore, NewUserService),
fx.Invoke(func(api *API) { api.Run() }),
)
app.Run() // manages lifecycle, but reflection-based
samber/do:
i := do.New()
do.Provide(i, NewConfig)
do.Provide(i, NewDatabase) // auto shutdown + health check
do.Provide(i, NewUserStore)
do.Provide(i, NewUserService)
api := do.MustInvoke[*API](i)
api.Run()
// defer i.Shutdown() — handles all cleanup automatically
Testing with DI
DI makes testing straightforward — inject mocks instead of real implementations:
// 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: How to use golang-dependency-injection on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add golang-dependency-injection
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches golang-dependency-injection from GitHub repository samber/cc-skills-golang and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate golang-dependency-injection. Access the skill through slash commands (e.g., /golang-dependency-injection) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★66 reviews- ★★★★★Chaitanya Patil· Dec 24, 2024
golang-dependency-injection reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kwame Rao· Dec 16, 2024
Useful defaults in golang-dependency-injection — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Kwame Patel· Dec 8, 2024
golang-dependency-injection has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Sakura Brown· Dec 4, 2024
Registry listing for golang-dependency-injection matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kwame Desai· Nov 27, 2024
golang-dependency-injection fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Lucas Nasser· Nov 23, 2024
Useful defaults in golang-dependency-injection — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Piyush G· Nov 15, 2024
I recommend golang-dependency-injection for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Diya Thomas· Nov 7, 2024
Registry listing for golang-dependency-injection matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Ava Robinson· Oct 26, 2024
golang-dependency-injection reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Diego Sanchez· Oct 18, 2024
We added golang-dependency-injection from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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