Implement Replit reference architecture with best-practice project layout. Use when designing new Replit integrations, reviewing project structure, or establishing architecture standards for Replit applications. Trigger with phrases like "replit architecture", "replit best practices", "replit project structure", "how to organize replit", "replit layout".
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
skills listSkill Instructions
name: replit-reference-architecture description: | Implement Replit reference architecture with best-practice project layout. Use when designing new Replit integrations, reviewing project structure, or establishing architecture standards for Replit applications. Trigger with phrases like "replit architecture", "replit best practices", "replit project structure", "how to organize replit", "replit layout". allowed-tools: Read, Grep version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io
Replit Reference Architecture
Overview
Production-ready architecture patterns for Replit integrations.
Prerequisites
- Understanding of layered architecture
- Replit SDK knowledge
- TypeScript project setup
- Testing framework configured
Project Structure
my-replit-project/
├── src/
│ ├── replit/
│ │ ├── client.ts # Singleton client wrapper
│ │ ├── config.ts # Environment configuration
│ │ ├── types.ts # TypeScript types
│ │ ├── errors.ts # Custom error classes
│ │ └── handlers/
│ │ ├── webhooks.ts # Webhook handlers
│ │ └── events.ts # Event processing
│ ├── services/
│ │ └── replit/
│ │ ├── index.ts # Service facade
│ │ ├── sync.ts # Data synchronization
│ │ └── cache.ts # Caching layer
│ ├── api/
│ │ └── replit/
│ │ └── webhook.ts # Webhook endpoint
│ └── jobs/
│ └── replit/
│ └── sync.ts # Background sync job
├── tests/
│ ├── unit/
│ │ └── replit/
│ └── integration/
│ └── replit/
├── config/
│ ├── replit.development.json
│ ├── replit.staging.json
│ └── replit.production.json
└── docs/
└── replit/
├── SETUP.md
└── RUNBOOK.md
Layer Architecture
┌─────────────────────────────────────────┐
│ API Layer │
│ (Controllers, Routes, Webhooks) │
├─────────────────────────────────────────┤
│ Service Layer │
│ (Business Logic, Orchestration) │
├─────────────────────────────────────────┤
│ Replit Layer │
│ (Client, Types, Error Handling) │
├─────────────────────────────────────────┤
│ Infrastructure Layer │
│ (Cache, Queue, Monitoring) │
└─────────────────────────────────────────┘
Key Components
Step 1: Client Wrapper
// src/replit/client.ts
export class ReplitService {
private client: ReplitClient;
private cache: Cache;
private monitor: Monitor;
constructor(config: ReplitConfig) {
this.client = new ReplitClient(config);
this.cache = new Cache(config.cacheOptions);
this.monitor = new Monitor('replit');
}
async get(id: string): Promise<Resource> {
return this.cache.getOrFetch(id, () =>
this.monitor.track('get', () => this.client.get(id))
);
}
}
Step 2: Error Boundary
// src/replit/errors.ts
export class ReplitServiceError extends Error {
constructor(
message: string,
public readonly code: string,
public readonly retryable: boolean,
public readonly originalError?: Error
) {
super(message);
this.name = 'ReplitServiceError';
}
}
export function wrapReplitError(error: unknown): ReplitServiceError {
// Transform SDK errors to application errors
}
Step 3: Health Check
// src/replit/health.ts
export async function checkReplitHealth(): Promise<HealthStatus> {
try {
const start = Date.now();
await replitClient.ping();
return {
status: 'healthy',
latencyMs: Date.now() - start,
};
} catch (error) {
return { status: 'unhealthy', error: error.message };
}
}
Data Flow Diagram
User Request
│
▼
┌─────────────┐
│ API │
│ Gateway │
└──────┬──────┘
│
▼
┌─────────────┐ ┌─────────────┐
│ Service │───▶│ Cache │
│ Layer │ │ (Redis) │
└──────┬──────┘ └─────────────┘
│
▼
┌─────────────┐
│ Replit │
│ Client │
└──────┬──────┘
│
▼
┌─────────────┐
│ Replit │
│ API │
└─────────────┘
Configuration Management
// config/replit.ts
export interface ReplitConfig {
apiKey: string;
environment: 'development' | 'staging' | 'production';
timeout: number;
retries: number;
cache: {
enabled: boolean;
ttlSeconds: number;
};
}
export function loadReplitConfig(): ReplitConfig {
const env = process.env.NODE_ENV || 'development';
return require(`./replit.${env}.json`);
}
Instructions
Step 1: Create Directory Structure
Set up the project layout following the reference structure above.
Step 2: Implement Client Wrapper
Create the singleton client with caching and monitoring.
Step 3: Add Error Handling
Implement custom error classes for Replit operations.
Step 4: Configure Health Checks
Add health check endpoint for Replit connectivity.
Output
- Structured project layout
- Client wrapper with caching
- Error boundary implemented
- Health checks configured
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Circular dependencies | Wrong layering | Separate concerns by layer |
| Config not loading | Wrong paths | Verify config file locations |
| Type errors | Missing types | Add Replit types |
| Test isolation | Shared state | Use dependency injection |
Examples
Quick Setup Script
# Create reference structure
mkdir -p src/replit/{handlers} src/services/replit src/api/replit
touch src/replit/{client,config,types,errors}.ts
touch src/services/replit/{index,sync,cache}.ts
Resources
Flagship Skills
For multi-environment setup, see replit-multi-env-setup.
More by jeremylongshore
View allRabbitmq Queue Setup - Auto-activating skill for Backend Development. Triggers on: rabbitmq queue setup, rabbitmq queue setup Part of the Backend Development skill category.
evaluating-machine-learning-models: This skill allows Claude to evaluate machine learning models using a comprehensive suite of metrics. It should be used when the user requests model performance analysis, validation, or testing. Claude can use this skill to assess model accuracy, precision, recall, F1-score, and other relevant metrics. Trigger this skill when the user mentions "evaluate model", "model performance", "testing metrics", "validation results", or requests a comprehensive "model evaluation".
building-neural-networks: This skill allows Claude to construct and configure neural network architectures using the neural-network-builder plugin. It should be used when the user requests the creation of a new neural network, modification of an existing one, or assistance with defining the layers, parameters, and training process. The skill is triggered by requests involving terms like "build a neural network," "define network architecture," "configure layers," or specific mentions of neural network types (e.g., "CNN," "RNN," "transformer").
Oauth Callback Handler - Auto-activating skill for API Integration. Triggers on: oauth callback handler, oauth callback handler Part of the API Integration skill category.
