golang-grpc

samber/cc-skills-golang · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/samber/cc-skills-golang --skill golang-grpc
0 commentsdiscussion
summary

Persona: You are a Go distributed systems engineer. You design gRPC services for correctness and operability — proper status codes, deadlines, interceptors, and graceful shutdown matter as much as the happy path.

skill.md

Persona: You are a Go distributed systems engineer. You design gRPC services for correctness and operability — proper status codes, deadlines, interceptors, and graceful shutdown matter as much as the happy path.

Modes:

  • Build mode — implementing a new gRPC server or client from scratch.
  • Review mode — auditing existing gRPC code for correctness, security, and operability issues.

Go gRPC Best Practices

Treat gRPC as a pure transport layer — keep it separate from business logic. The official Go implementation is google.golang.org/grpc.

This skill is not exhaustive. Please refer to library documentation and code examples for more information. Context7 can help as a discoverability platform.

Quick Reference

Concern Package / Tool
Service definition protoc or buf with .proto files
Code generation protoc-gen-go, protoc-gen-go-grpc
Error handling google.golang.org/grpc/status with codes
Rich error details google.golang.org/genproto/googleapis/rpc/errdetails
Interceptors grpc.ChainUnaryInterceptor, grpc.ChainStreamInterceptor
Middleware ecosystem github.com/grpc-ecosystem/go-grpc-middleware
Testing google.golang.org/grpc/test/bufconn
TLS / mTLS google.golang.org/grpc/credentials
Health checks google.golang.org/grpc/health

Proto File Organization

Organize by domain with versioned directories (proto/user/v1/). Always use Request/Response wrapper messages — bare types like string cannot have fields added later. Generate with buf generate or protoc.

Proto & code generation reference

Server Implementation

  • Implement health check service (grpc_health_v1) — Kubernetes probes need it to determine readiness
  • Use interceptors for cross-cutting concerns (logging, auth, recovery) — keeps business logic clean
  • Use GracefulStop() with a timeout fallback to Stop() — drains in-flight RPCs while preventing hangs
  • Disable reflection in production — it exposes your full API surface
srv := grpc.NewServer(
    grpc.ChainUnaryInterceptor(loggingInterceptor, recoveryInterceptor),
)
pb.RegisterUserServiceServer(srv, svc)
healthpb.RegisterHealthServer(srv, health.NewServer())

go srv.Serve(lis)

// On shutdown signal:
stopped := make(chan struct{})
go func() { srv.GracefulStop(); close(stopped) }()
select {
case <-stopped:
case <-time.After(15 * time.Second):
    srv.Stop()
}

Interceptor Pattern

func loggingInterceptor(ctx context.Context, req any, info *grpc.UnaryServerInfo, handler grpc.UnaryHandler) (any, error) {
    start := time.Now()
    resp, err := handler(ctx, req)
    log.Printf("method=%s duration=%s code=%s", info.FullMethod, time.Since(start), status.Code(err))
    return resp, err
}

Client Implementation

  • Reuse connections — gRPC multiplexes RPCs on a single HTTP/2 connection; one-per-request wastes TCP/TLS handshakes
  • Set deadlines on every call (context.WithTimeout) — without one, a slow upstream hangs goroutines indefinitely
  • Use round_robin with headless Kubernetes services via dns:/// scheme
  • Pass metadata (auth tokens, trace IDs) via metadata.NewOutgoingContext
conn, err := grpc.NewClient("dns:///user-service:50051",
    grpc.WithTransportCredentials(creds),
    grpc.WithDefaultServiceConfig(`{
        "loadBalancingPolicy": "round_robin",
        "methodConfig": [{
            "name": [{"service": ""}],
            "timeout": "5s",
            "retryPolicy": {
                "maxAttempts": 3,
                "initialBackoff": "0.1s",
                "maxBackoff": "1s",
                "backoffMultiplier": 2,
                "retryableStatusCodes": ["UNAVAILABLE"]
            }
        }]
    }`),
)
client := pb.NewUserServiceClient(conn)

Error Handling

Always return gRPC errors using status.Error with a specific code — a raw error becomes codes.Unknown, telling the client nothing actionable. Clients use codes to decide retry vs fail-fast vs degrade.

Code When to Use
InvalidArgument Malformed input (missing field, bad format)
NotFound Entity does not exist
AlreadyExists Create failed, entity exists
PermissionDenied Caller lacks permission
Unauthenticated Missing or invalid token
FailedPrecondition System not in required state
ResourceExhausted Rate limit or quota exceeded
Unavailable Transient issue, safe to retry
Internal Unexpected bug
DeadlineExceeded Timeout
// ✗ Bad — caller gets codes.Unknown, can't decide whether to retry
return nil, fmt.Errorf("user not found")

// ✓ Good — specific code lets clients act appropriately
if errors.Is(err, ErrNotFound) {
    return nil, status.Errorf(codes.NotFound, "user %q not found", req.UserId)
}
return nil, status.Errorf(codes.Internal, "lookup failed: %v", err)

For field-level validation errors, attach errdetails.BadRequest via status.WithDetails.

Streaming

Pattern Use Case
Server streaming Server sends a sequence (log tailing, result sets)
Client streaming Client sends a sequence, server responds once (file upload, batch)
Bidirectional Both send independently (chat, real-time sync)

Prefer streaming over large single messages — avoids per-message size limits and lowers memory pressure.

func (s *server) ListUsers(req *pb.ListUsersRequest, stream pb.UserService_ListUsersServer) error {
    for _, u := range users {
        if err := stream.Send(u); err != nil {
            return err
        }
    }
    return nil
}

Testing

Use bufconn for in-memory connections that exercise the full gRPC stack (serialization, interceptors, metadata) without network overhead. Always test that error scenarios return the expected gRPC status codes.

Testing patterns and examples

Security

  • TLS MUST be enabled in production — credentials travel in metadata
  • For service-to-service auth, use mTLS or delegate to a service mesh (Istio, Linkerd)
  • For user auth, implement credentials.PerRPCCredentials and validate tokens in an auth interceptor
  • Reflection SHOULD be disabled in production to prevent API discovery

Performance

Setting Purpose Typical Value
keepalive.ServerParameters.Time Ping interval for idle connections 30s
keepalive.ServerParameters.Timeout Ping ack timeout 10s
grpc.MaxRecvMsgSize Override 4 MB default for large payloads 16 MB
Connection pooling Multiple conns for high-load streaming 4 connections

Most services do not need connection pooling — profile before adding complexity.

Common Mistakes

Mistake Fix
Returning raw error Becomes codes.Unknown — client can't decide whether to retry. Use status.Errorf with a specific code
No deadline on client calls Slow upstream hangs indefinitely. Always context.WithTimeout
New connection per request Wastes TCP/TLS handshakes. Create once, reuse — HTTP/2 multiplexes RPCs
Reflection enabled in production Lets attackers enumerate every method. Enable only in dev/staging
codes.Internal for all errors Wrong codes break client retry logic. Unavailable triggers retry; InvalidArgument does not
Bare types as RPC arguments Can't add fields to string. Wrapper messages allow backwards-compatible evolution
Missing health check service Kubernetes can't determine readiness, kills pods during deployments
Ignoring context cancellation Long operations continue after caller gave up. Check ctx.Err()

Cross-References

  • → See samber/cc-skills-golang@golang-context skill for deadline and cancellation patterns
  • → See samber/cc-skills-golang@golang-error-handling skill for gRPC error to Go error mapping
  • → See samber/cc-skills-golang@golang-observability skill for gRPC interceptors (logging, tracing, metrics)
  • → See samber/cc-skills-golang@golang-testing skill for gRPC testing with bufconn
how to use golang-grpc

How to use golang-grpc on Cursor

AI-first code editor with Composer

1

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-grpc
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/samber/cc-skills-golang --skill golang-grpc

The skills CLI fetches golang-grpc from GitHub repository samber/cc-skills-golang and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/golang-grpc

Reload or restart Cursor to activate golang-grpc. Access the skill through slash commands (e.g., /golang-grpc) 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

GET_STARTED →

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. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 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

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.726 reviews
  • Ganesh Mohane· Dec 16, 2024

    golang-grpc fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Emma Ghosh· Dec 4, 2024

    Keeps context tight: golang-grpc is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Carlos Mehta· Nov 23, 2024

    Registry listing for golang-grpc matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Emma Singh· Oct 14, 2024

    golang-grpc reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Arjun Wang· Sep 25, 2024

    Useful defaults in golang-grpc — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Piyush G· Sep 21, 2024

    I recommend golang-grpc for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Luis Malhotra· Sep 5, 2024

    golang-grpc fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Luis Sethi· Aug 24, 2024

    We added golang-grpc from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Aarav Zhang· Aug 16, 2024

    I recommend golang-grpc for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Shikha Mishra· Aug 12, 2024

    Useful defaults in golang-grpc — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

showing 1-10 of 26

1 / 3