cloudflare-workers
Cloudflare Workers patterns for Worker runtime APIs, Durable Objects, KV, R2, D1, Queues, WebSockets, streaming responses, bindings, wrangler configuration, and deployment limits. Use when users mention Cloudflare Workers, Durable Objects, KV, R2, D1, Queues, wrangler, or edge runtime behavior.
Works with
--- name: cloudflare-workers description: Cloudflare Workers patterns for Worker runtime APIs, Durable Objects, KV, R2, D1, Queues, WebSockets, streaming responses, bindings, wrangler configuration, and deployment limits. Use when users mention Cloudflare Workers, Durable Objects, KV, R2, D1, Queues, wrangler, or edge runtime behavior. license: MIT --- # Cloudflare Workers ## Reference Repositories - [Cloudflare Docs](https://github.com/cloudflare/cloudflare-docs) - Workers, Durable Objects, KV, R2, D1, Queues, WebSockets, bindings, and deployment docs - [Hono](https://github.com/honojs/hono) - TypeScript web framework commonly used on Workers ## Upstream Grounding When Worker runtime behavior, bindings, Durable Objects, WebSockets, streaming, cache APIs, service bindings, compatibility dates, limits, or wrangler configuration affect correctness, ask DeepWiki a narrow question against `cloudflare/cloudflare-docs` before relying on memory. Use `honojs/hono` as the grounding repo when the question is about Hono on Workers. Verify decisive details against local generated Worker types, source, or official Cloudflare docs before changing code. Skip DeepWiki for stable Web API basics and repo-local deployment patterns already visible in the code. ## When to Apply This Skill Use this pattern when you need to: - Work on `apps/api` Worker code, bindings, or `wrangler` configuration. - Implement or debug Durable Objects, KV, R2, D1, Queues, or WebSockets. - Handle streaming responses, SSE, CORS, cache behavior, or request lifecycle limits. - Check Cloudflare-specific runtime behavior or deployment constraints. ## Request Lifecycle Rules - Every async side effect must be awaited, returned, or passed to `c.executionCtx.waitUntil(...)`. Floating promises are unsafe because the isolate can stop after the response. - Call `waitUntil` as a method on `c.executionCtx`. Do not destructure it. - Keep `waitUntil` work bounded and best-effort. Use Queues for guaranteed or long-running work. - For Hyperdrive plus `pg`, create a fresh `pg.Client` per request and close it after all queued work that uses the client settles. Hyperdrive is the pool. - Node-style database drivers require `nodejs_compat` in Worker configuration. - Skip generic response-header middleware, including CORS, for WebSocket upgrade requests. The `101` response headers are immutable. - Put stateful or long-lived WebSockets in Durable Objects. Prefer hibernation-aware APIs when the object owns many idle sockets. - Trust generated Worker binding types such as `Cloudflare.Env`; regenerate them when bindings or `wrangler` config change.
More Deployment & CI/CD skills
azure-enterprise-infra-planner
microsoft/azure-skills
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.
azure-kubernetes-app-deploy
microsoft/azure-skills
Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
finetuning
microsoft/azure-skills
Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).

