Loading...
Loading...
Found 92 Skills
Cloudflare Workers Runtime APIs including Fetch, Streams, Crypto, Cache, WebSockets, and Encoding. Use for HTTP requests, streaming, encryption, caching, real-time connections, or encountering API compatibility, response handling, stream processing errors.
Migrate to Cloudflare Workers from AWS Lambda, Vercel, Express, and Node.js. Use when porting existing applications to the edge, adapting serverless functions, or resolving Node.js API compatibility issues.
Complete knowledge domain for Cloudflare Workers AI - Run AI models on serverless GPUs across Cloudflare's global network. Use when: implementing AI inference on Workers, running LLM models, generating text/images with AI, configuring Workers AI bindings, implementing AI streaming, using AI Gateway, integrating with embeddings/RAG systems, or encountering "AI_ERROR", rate limit errors, model not found, token limit exceeded, or neurons exceeded errors. Keywords: workers ai, cloudflare ai, ai bindings, llm workers, @cf/meta/llama, workers ai models, ai inference, cloudflare llm, ai streaming, text generation ai, ai embeddings, image generation ai, workers ai rag, ai gateway, llama workers, flux image generation, stable diffusion workers, vision models ai, ai chat completion, AI_ERROR, rate limit ai, model not found, token limit exceeded, neurons exceeded, ai quota exceeded, streaming failed, model unavailable, workers ai hono, ai gateway workers, vercel ai sdk workers, openai compatible workers, workers ai vectorize
Cloudflare Workers integration. Manage data, records, and automate workflows. Use when the user wants to interact with Cloudflare Workers data.
Cloudflare Workers local development with Wrangler, Miniflare, hot reload, debugging. Use for project setup, wrangler.jsonc configuration, or encountering local dev, HMR, binding simulation errors.
Complete CI/CD guide for Cloudflare Workers using GitHub Actions and GitLab CI. Use for automated testing, deployment pipelines, preview environments, secrets management, or encountering deployment failures, workflow errors, environment configuration issues.
Run LLMs and AI models on Cloudflare's GPU network with Workers AI. Includes Llama 4, Gemma 3, Mistral 3.1, Flux images, BGE embeddings, streaming, and AI Gateway. Handles 2025 breaking changes. Prevents 7 documented errors. Use when: implementing LLM inference, images, RAG, or troubleshooting AI_ERROR, rate limits, max_tokens, BGE pooling, context window, neuron billing, Miniflare AI binding, NSFW filter, num_steps.
Multi-language Workers development with Rust, Python, and WebAssembly. Use when building Workers in languages other than JavaScript/TypeScript, or when integrating WASM modules for performance-critical code.
Rapid development with Cloudflare Workers - build and deploy serverless applications on Cloudflare's global network. Use when building APIs, full-stack web apps, edge functions, background jobs, or real-time applications. Triggers on phrases like "cloudflare workers", "wrangler", "edge computing", "serverless cloudflare", "workers bindings", or files like wrangler.toml, worker.ts, worker.js.
Build serverless applications on Cloudflare Workers. Covers runtime APIs, handlers (fetch, scheduled, queue, email), bindings (KV, R2, D1, Durable Objects, Queues, AI, Vectorize), wrangler.toml configuration, local development with Miniflare, static assets, compatibility flags, testing with Vitest. Keywords: Cloudflare Workers, serverless, edge computing, Wrangler, fetch handler, scheduled handler, bindings, KV, R2, D1, Durable Objects, Workers AI, Miniflare, wrangler.toml, compatibility_date.
Cloudflare Workers AI for serverless GPU inference. Use for LLMs, text/image generation, embeddings, or encountering AI_ERROR, rate limits, token exceeded errors.
Cloudflare Workers performance optimization with CPU, memory, caching, bundle size. Use for slow workers, high latency, cold starts, or encountering CPU limits, memory issues, timeout errors.