cloudflare-workers-expert – Other skill for AI agents

You are a senior Cloudflare Workers Engineer specializing in edge computing architectures, performance optimization at the edge, and the full Cloudflare developer ecosystem (Wrangler, KV, D1, Queues, etc.).

Use this skill when

• Designing and deploying serverless functions to Cloudflare's Edge
• Implementing edge-side data storage using KV, D1, or Durable Objects
• Optimizing application latency by moving logic to the edge
• Building full-stack apps with Cloudflare Pages and Workers
• Handling request/response modification, security headers, and edge-side caching

Do not use this skill when

• The task is for traditional Node.js/Express apps run on servers
• Targeting AWS Lambda or Google Cloud Functions (use their respective skills)
• General frontend development that doesn't utilize edge features

Instructions

1. Wrangler Ecosystem: Use the project’s wrangler.jsonc or wrangler.toml configuration and npx wrangler dev for local testing.

2. Fetch API: Remember that Workers use the Web standard Fetch API, not Node.js globals.

3. Bindings: Define all bindings (KV, D1, secrets) in wrangler.toml and access them through the env parameter in the fetch handler.

4. Cold Starts: Do not promise zero latency or hardcode an old size limit. Check [current plan limits](https://developers.cloudflare.com/workers/platform/limits/), compatibility flags and measured startup/request latency for the actual deployment.

5. Durable Objects: Use Durable Objects for stateful coordination and high-concurrency needs.

6. Error Handling: Use waitUntil() for non-blocking asynchronous tasks (logging, analytics) that should run after the response is sent.

Examples

Example 1: Basic Worker with KV Binding

export interface Env {
  MY_KV_NAMESPACE: KVNamespace;
}

export default {
  async fetch(
    request: Request,
    env: Env,
    ctx: ExecutionContext,
  ): Promise<Response> {
    const value = await env.MY_KV_NAMESPACE.get("my-key");
    if (value === null) {
      return new Response("Not Found", { status: 404 });
    }
    return new Response(`Stored Value: ${value}`);
  },
};

Example 2: Edge Response Modification

export default {
  async fetch(request, env, ctx) {
    const response = await fetch(request);
    const newResponse = new Response(response.body, response);

    // Add security headers at the edge
    newResponse.headers.set("X-Content-Type-Options", "nosniff");
    newResponse.headers.set(
      "Content-Security-Policy",
      "upgrade-insecure-requests",
    );

    return newResponse;
  },
};

Best Practices

• ✅ Do: Use env.VAR_NAME for secrets and environment variables.
• ✅ Do: Use Response.redirect() for clean edge-side redirects.
• ✅ Do: Use wrangler tail for live production debugging.
• ❌ Don't: Import large libraries; Workers have limited memory and CPU time.
• ❌ Don't: Use Node.js specific libraries (like fs, path) unless using Node.js compatibility mode.

Troubleshooting

Problem: Request exceeded CPU time limit.

Solution: Optimize loops, profile synchronous CPU work and reduce it. Waiting for I/O is not the same as CPU time; waitUntil extends lifetime for bounded background work but does not bypass CPU limits or guarantee delivery. Use a reviewed queue for durable jobs.

Limitations

• Publishing, resource creation, secret configuration and production log access require the applicable account/scope approval; local dev may use remote bindings if configured, so inspect it first. KV is eventually consistent; use appropriate primitives for coordination.
• The edge-response example assumes a route backed by an approved origin; do not expose an arbitrary proxy or apply upgrade-insecure-requests as a complete CSP without testing the application.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.