How does it handle CORS?

The skill provides a standardized middleware pattern for handling CORS headers and preflight OPTIONS requests across your Cloudflare Worker routes.

Can I use this for multi-worker setups?

Absolutely. The skill includes specific patterns for shared workspaces and zero-latency internal communication using service bindings.

Does it include AI integration guidance?

Yes, it covers Workers AI for embeddings and inference, and explains how to integrate Vectorize for semantic search and RAG workflows.

Does this skill support local development?

Yes, it provides instructions for using Wrangler for local emulation of KV, D1, and R2, as well as remote development strategies for AI and Vectorize features.

What databases does it cover?

It focuses primarily on Cloudflare D1 for relational SQL data, but also provides logic for choosing KV for caching or R2 for large object storage.

Cloudflare Full-Stack Architect

Name: Cloudflare Full-Stack Architect
Author: paolomoz

bypaolomoz

•

Cloud Infrastructure

Builds production-ready full-stack applications on the Cloudflare edge platform using Workers, D1, R2, and AI bindings.

This skill provides comprehensive guidance for architecting and deploying full-stack applications on Cloudflare's serverless infrastructure. It covers everything from project directory structuring and wrangler.toml configuration to implementing sophisticated multi-worker communications and choosing the right storage solutions like D1 for SQL, KV for caching, and R2 for object storage. It is particularly useful for developers looking to leverage edge computing, semantic search with Vectorize, or integrated AI inference without the overhead of traditional server management.

Key Features

01Optimized project structure for single and multi-worker architectures

02Strict TypeScript Env typing and @cloudflare/workers-types integration

032 GitHub stars

04Zero-latency multi-worker communication via service bindings

05Production-grade wrangler.toml configuration for storage and AI bindings

06Performance-focused storage selection and implementation patterns

Use Cases

01Implementing RAG applications using Vectorize and Workers AI at the edge

02Building serverless APIs with relational data using D1 and Workers

03Migrating existing Node.js/Express applications to high-performance edge workers

Key Features

01Optimized project structure for single and multi-worker architectures

02Strict TypeScript Env typing and @cloudflare/workers-types integration

032 GitHub stars

04Zero-latency multi-worker communication via service bindings

05Production-grade wrangler.toml configuration for storage and AI bindings

06Performance-focused storage selection and implementation patterns

Use Cases

01Implementing RAG applications using Vectorize and Workers AI at the edge

02Building serverless APIs with relational data using D1 and Workers

03Migrating existing Node.js/Express applications to high-performance edge workers