external/cc-skills-golang/golang-dependency-injection/SKILL.md
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.
npx skillsauth add seikaikyo/dash-skills golang-dependency-injectionInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
Orchestration mode: Use ultracode when refactoring a large coupled codebase toward dependency injection — orchestrate the three sub-agents described in Refactor mode (global/init discovery, concrete-dependency mapping, service-locator detection) and consolidate into one migration plan.
Modes:
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 (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.
init() for service setupmain() or app startup) — NEVER pass the container as a dependency| 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.
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:
Go has three main approaches to DI libraries:
| 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 |
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 lifecycle hooks (OnStart/OnStop) or health checks; cleanup via returned func() from providers
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
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: "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")
}
}
Container cloning creates an isolated copy where you override only the services you need to mock:
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).
| Signal | Action | | --- | --- | | < 10 services, simple dependencies | Stay with manual constructor injection | | 10-20 services, some cross-cutting concerns | Consider a DI library | | 20+ services, lifecycle management needed | Strongly recommended | | Need health checks, graceful shutdown | Use a library with built-in lifecycle support | | Team unfamiliar with DI concepts | Start manual, migrate incrementally |
| Mistake | Fix |
| --- | --- |
| Global variables as dependencies | Pass through constructors or DI container |
| init() for service setup | Explicit initialization in main() or container |
| Depending on concrete types | Accept 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 request | One container per application; use scopes for request-level isolation |
samber/cc-skills-golang@golang-samber-do skill for detailed samber/do usage patternssamber/cc-skills-golang@golang-structs-interfaces skill for interface design and compositionsamber/cc-skills-golang@golang-testing skill for testing with dependency injectionsamber/cc-skills-golang@golang-project-layout skill for DI initialization placementtools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.