一键导入
cloudflare-workers-expert
Expert in Cloudflare Workers and the Edge Computing ecosystem. Covers Wrangler, KV, D1, Durable Objects, and R2 storage.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Expert in Cloudflare Workers and the Edge Computing ecosystem. Covers Wrangler, KV, D1, Durable Objects, and R2 storage.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Win32 FFI binding lifecycle for @bun-win32/* packages (Win32 DLL bindings via bun:ffi on Windows). Use when generating a new package from a DLL, auditing FFI↔TS↔header consistency, fixing nullability (| NULL / | 0n), or understanding the bootstrap→catalog→stub→audit→nullcheck pipeline. Covers 117 packages; strict TypeScript; Bun runtime; Biome formatting.
Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks.
Suite of tools for creating elaborate, multi-component HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.
Builds AI agents on Cloudflare using the Agents SDK with state management, real-time WebSockets, scheduled tasks, tool integration, and chat capabilities. Generates production-ready agent code deployed to Workers. Use when: user wants to "build an agent", "AI agent", "chat agent", "stateful agent", mentions "Agents SDK", needs "real-time AI", "WebSocket AI", or asks about agent "state management", "scheduled tasks", or "tool calling".
Builds remote MCP (Model Context Protocol) servers on Cloudflare Workers with tools, OAuth authentication, and production deployment. Generates server code, configures auth providers, and deploys to Workers. Use when: user wants to "build MCP server", "create MCP tools", "remote MCP", "deploy MCP", add "OAuth to MCP", or mentions Model Context Protocol on Cloudflare. Also triggers on "MCP authentication" or "MCP deployment".
Create optimized production bundles with Bun's native bundler. Use when building applications for production, optimizing bundle sizes, setting up multi-environment builds, or replacing webpack/esbuild/rollup.
| name | cloudflare-workers-expert |
| description | Expert in Cloudflare Workers and the Edge Computing ecosystem. Covers Wrangler, KV, D1, Durable Objects, and R2 storage. |
| risk | safe |
| source | community |
| date_added | 2026-02-27 |
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.).
wrangler.toml for configuration and npx wrangler dev for local testing.wrangler.toml and access them through the env parameter in the fetch handler.waitUntil() for non-blocking asynchronous tasks (logging, analytics) that should run after the response is sent.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) {
return new Response("Not Found", { status: 404 });
}
return new Response(`Stored Value: ${value}`);
},
};
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;
},
};
env.VAR_NAME for secrets and environment variables.Response.redirect() for clean edge-side redirects.wrangler tail for live production debugging.fs, path) unless using Node.js compatibility mode.Problem: Request exceeded CPU time limit.
Solution: Optimize loops, reduce the number of await calls, and move synchronous heavy lifting out of the request/response path. Use ctx.waitUntil() for tasks that don't block the response.