rust-architect

🥈Silver

@nanlong

Rust Architect skills for Claude Code

600Updated 2w ago

Intermediate30min to implementautomation

Saves ~240 min per use

Quick InstallView Source

git clone https://github.com/nanlong/rust-architect.git

Works with:

Claude

Overview

About This Skill

Rust Architect skills for Claude Code

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/nanlong/rust-architect

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Act as a Rust Architect. Design a robust, scalable system for [COMPANY] in the [INDUSTRY] sector. The system should handle [DATA] with the following requirements: [REQUIREMENTS]. Provide a detailed architecture diagram, key components, and technology stack recommendations.

Example Output

# Rust System Architecture for GreenTech Solutions

## Overview
A scalable IoT data processing system for GreenTech Solutions, handling sensor data from 10,000+ devices with real-time analytics and predictive maintenance capabilities.

## Architecture Diagram
```mermaid
flowchart TD
    A[IoT Devices] --> B[Edge Nodes]
    B --> C[Data Ingestion Layer]
    C --> D[Processing Cluster]
    D --> E[Storage Layer]
    D --> F[Analytics Engine]
    E --> G[API Gateway]
    F --> G
    G --> H[Dashboard]
```

## Key Components
- **Edge Nodes**: Rust-based lightweight processors for initial data filtering
- **Data Ingestion Layer**: Kafka cluster for high-throughput message handling
- **Processing Cluster**: Kubernetes-managed Rust services for parallel data processing
- **Storage Layer**: Time-series database (InfluxDB) with Rust client libraries
- **Analytics Engine**: Machine learning models integrated with Rust's ndarray and linfa crates

## Technology Stack
- **Programming Language**: Rust (with tokio for async processing)
- **Message Broker**: Apache Kafka
- **Containerization**: Docker
- **Orchestration**: Kubernetes
- **Database**: InfluxDB
- **Monitoring**: Prometheus with Rust exporters

## Performance Considerations
- Designed to handle 100,000+ messages per second
- Sub-millisecond latency for critical path operations
- Automatic scaling based on load metrics

## Security
- End-to-end encryption using Rust's ring crate
- Role-based access control implemented at API gateway
- Regular security audits using Rust's built-in tools