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/grpc-service-development

Build high-performance gRPC services with Protocol Buffers, bidirectional streaming, and microservice communication. Use when building gRPC servers, defining service contracts, or implementing inter-service communication.

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useful-ai-prompts
309200 skills
Install
$ npx -y skills add aj-geddes/useful-ai-prompts --skill grpc-service-development --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/grpc-service-development

Context preview

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Build high-performance gRPC services with Protocol Buffers, bidirectional streaming, and microservice communication. Use when building gRPC servers, defining service contracts, or implementing inter-service communication.

SKILL.md

grpc-service-development.SKILL.md
name: grpc-service-development
description: >
  Build high-performance gRPC services with Protocol Buffers, bidirectional
  streaming, and microservice communication. Use when building gRPC servers,
  defining service contracts, or implementing inter-service communication.

gRPC Service Development

Table of Contents

  • [Overview](#overview)
  • [When to Use](#when-to-use)
  • [Quick Start](#quick-start)
  • [Reference Guides](#reference-guides)
  • [Best Practices](#best-practices)

Overview

Develop efficient gRPC services using Protocol Buffers for service definition, with support for unary calls, client streaming, server streaming, and bidirectional streaming patterns.

When to Use

  • Building microservices that require high performance
  • Defining service contracts with Protocol Buffers
  • Implementing real-time bidirectional communication
  • Creating internal service-to-service APIs
  • Optimizing bandwidth-constrained environments
  • Building polyglot service architectures

Quick Start

Minimal working example:

syntax = "proto3";

package user.service;

message User {
  string id = 1;
  string email = 2;
  string first_name = 3;
  string last_name = 4;
  string role = 5;
  int64 created_at = 6;
  int64 updated_at = 7;
}

message CreateUserRequest {
  string email = 1;
  string first_name = 2;
  string last_name = 3;
  string role = 4;
}

message UpdateUserRequest {
  string id = 1;
  string email = 2;
  string first_name = 3;
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the `references/` directory:

| Guide | Contents | |---|---| | [Protocol Buffer Service Definition](references/protocol-buffer-service-definition.md) | Protocol Buffer Service Definition | | [Node.js gRPC Server Implementation](references/nodejs-grpc-server-implementation.md) | Node.js gRPC Server Implementation | | [Python gRPC Server (grpcio)](references/python-grpc-server-grpcio.md) | Python gRPC Server (grpcio) | | [Client Implementation](references/client-implementation.md) | Client Implementation |

Best Practices

✅ DO

  • Use clear message and service naming
  • Implement proper error handling with gRPC status codes
  • Add metadata for logging and tracing
  • Version your protobuf definitions
  • Use streaming for large datasets
  • Implement timeouts and deadlines
  • Monitor gRPC metrics

❌ DON'T

  • Use gRPC for browser-based clients (use gRPC-Web)
  • Expose sensitive data in proto definitions
  • Create deeply nested messages
  • Ignore error status codes
  • Send uncompressed large payloads
  • Skip security with TLS in production
Read more
Ships withuseful-ai-prompts

488 production-ready AI prompts, all following a standardized template with validated quality gates. Transform ChatGPT, Claude, and other AI assistants into expert consultants.

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