ashish7802 Cloudflare Workers Skill
Build serverless applications and deploy globally across the Cloudflare edge network.
Ecosystem Graph Preview
graph LR
cloudflare-workers["cloudflare-workers"]:::core
classDef core fill:#f9f,stroke:#333,stroke-width:4px;
cloudflare-workers -- "works well with" --> hono
cloudflare-workers -- "integrates with" --> drizzle
deno-deploy -- "alternative to" --> cloudflare-workers
Recommended Next Skills
- deno-deploy (Score: 0.82) Why: Direct relationship, Both are Cloud, Shared ecosystem (javascript), Similar network profile
- drizzle (Score: 0.8) Why: Direct relationship, Both are Developer Tools, Can deploy to cloudflare
- hono (Score: 0.72) Why: Direct relationship, Shared ecosystem (javascript), Can deploy to cloudflare, Similar network profile
Quick Start
Workers run V8 isolates, meaning there are virtually zero cold starts compared to AWS Lambda. Your code executes physically close to the user in hundreds of data centers globally.
npm create cloudflare@latest
Production Patterns
KV and Durable Objects
Workers are stateless. To persist data at the edge, use Cloudflare KV for read-heavy eventual consistency, or Durable Objects for strongly consistent transactional state (like WebSockets or counters).
Architecture & Scaling
Web Standard APIs
Workers do not run Node.js (though compatibility is improving). You must use Web Standard APIs (fetch, Request, Response, crypto.subtle). Avoid libraries that depend heavily on fs or native Node C++ bindings.
Error Recovery
Workers have strict CPU time limits (e.g., 10-50ms). Doing heavy CPU processing will cause the worker to be killed. Offload heavy processing to traditional servers or use Cloudflare Queues.
Security Notes
Use wrangler secret put to securely store API keys. These are injected into the env object passed to your fetch handler, ensuring secrets never touch the codebase.
References
Why use this skill
Use this when your agent works with cloudflare-workers — structured patterns beat pasted docs and prevent common hallucinations.
AI pitfalls
- Referencing CLI flags or config keys that do not exist
- Using outdated major versions of tools
- Skipping lockfile or version pinning in examples
Production checklist
- Secrets in environment variables, not source code
- Error handling and logging in place
- Rate limits and timeouts configured
Related skills
Last Verified: 2026-07-02