gRPC Golang (gRPC-Go)

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/grpc-golang

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

gRPC Golang (gRPC-Go)

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Designing microservices communication with gRPC in Go.
• Building high-performance internal APIs using Protobuf.
• Implementing streaming workloads (unidirectional or bidirectional).
• Standardizing API contracts using Protobuf and Buf.
• Configuring mTLS for service-to-service authentication.
• Building pure REST/HTTP public APIs without gRPC requirements.

Operating Table

metadata.json

ORIGIN.md

resources/implementation-playbook.md

resources/implementation-playbook.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm Technical Context: Identify Go version, gRPC-Go version, and whether the project uses Buf or raw protoc.
2. Confirm Requirements: Identify mTLS needs, load patterns (unary/streaming), SLOs, and message size limits.
3. Plan Schema: Define package versioning (e.g., api.v1), resource types, and error mapping.
4. Security Design: Implement mTLS for service-to-service authentication.
5. Observability: Configure interceptors for tracing, metrics, and structured logging.
6. Verification: Always run buf lint and breaking change checks before finalizing code generation.
7. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.

Imported Workflow Notes

Imported: Step-by-Step Guide

1. Confirm Technical Context: Identify Go version, gRPC-Go version, and whether the project uses Buf or raw protoc.
2. Confirm Requirements: Identify mTLS needs, load patterns (unary/streaming), SLOs, and message size limits.
3. Plan Schema: Define package versioning (e.g.,

   api.v1

   ), resource types, and error mapping.
4. Security Design: Implement mTLS for service-to-service authentication.
5. Observability: Configure interceptors for tracing, metrics, and structured logging.
6. Verification: Always run

   buf lint

   and breaking change checks before finalizing code generation.

Refer to

resources/implementation-playbook.md

Imported: Overview

Comprehensive guide for designing and implementing production-grade gRPC services in Go. Covers contract standardization with Buf, transport layer security via mTLS, and deep observability with OpenTelemetry interceptors.

Imported: Limitations

• Does not cover service mesh traffic routing (Istio/Linkerd configuration).
• Does not cover gRPC-Web or browser-based gRPC integration.
• Assumes Go 1.21+ and gRPC-Go v1.60+; older versions may have different APIs (e.g.,

  grpc.Dial

  vs

  grpc.NewClient

  ).
• Does not cover L7 gRPC-aware load balancer configuration (e.g., Envoy, NGINX).
• Does not address Protobuf schema registry or large-scale schema governance beyond Buf lint.

Examples

Example 1: Ask for the upstream workflow directly

Use @grpc-golang to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @grpc-golang against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @grpc-golang for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @grpc-golang using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Examples

Example 1: Defining a Service & Message (v1 API)

syntax = "proto3";
package api.v1;
option go_package = "github.com/org/repo/gen/api/v1;apiv1";

service UserService {
  rpc GetUser(GetUserRequest) returns (GetUserResponse);
}

message User {
  string id = 1;
  string name = 2;
}

message GetUserRequest {
  string id = 1;
}

message GetUserResponse {
  User user = 1;
}

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• ✅ Do: Use Buf to standardize your toolchain and linting with buf.yaml and buf.gen.yaml.
• ✅ Do: Always use semantic versioning in package paths (e.g., package api.v1).
• ✅ Do: Enforce mTLS for all internal service-to-service communication.
• ✅ Do: Handle ctx.Done() in all streaming handlers to prevent resource leaks.
• ✅ Do: Map domain errors to standard gRPC status codes (e.g., codes.NotFound).
• ❌ Don't: Return raw internal error strings or stack traces to gRPC clients.
• ❌ Don't: Create a new grpc.ClientConn per request; always reuse connections.

Imported Operating Notes

Imported: Best Practices

• ✅ Do: Use Buf to standardize your toolchain and linting with

  buf.yaml

  and

  buf.gen.yaml

  .
• ✅ Do: Always use semantic versioning in package paths (e.g.,

  package api.v1

  ).
• ✅ Do: Enforce mTLS for all internal service-to-service communication.
• ✅ Do: Handle

  ctx.Done()

  in all streaming handlers to prevent resource leaks.
• ✅ Do: Map domain errors to standard gRPC status codes (e.g.,

  codes.NotFound

  ).
• ❌ Don't: Return raw internal error strings or stack traces to gRPC clients.
• ❌ Don't: Create a new

  grpc.ClientConn

  per request; always reuse connections.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/grpc-golang

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Imported Troubleshooting Notes

Imported: Troubleshooting

• Error: Inconsistent Gen: If the generated code does not match the schema, run

  buf generate

  and verify the

  go_package

  option.
• Error: Context Deadline: Check client timeouts and ensure the server is not blocking infinitely in streaming handlers.
• Error: mTLS Handshake: Ensure the CA certificate is correctly added to the

  x509.CertPool

  on both client and server sides.

Related Skills

• @github-issue-creator

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @github-workflow-automation

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @gitlab-automation

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @gitlab-ci-patterns

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

• implementation-playbook.md

Imported Reference Notes

Imported: Resources

• resources/implementation-playbook.md

  for detailed patterns, code examples, and anti-patterns.
• Google API Design Guide
• Buf Docs
• gRPC-Go Docs
• OpenTelemetry Go Instrumentation