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Cloudflare Deploy

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mizchi
cloudflare-deploy

Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.

Overview

Publishermizchi
Repositoryskills
Skill namecloudflare-deploy
Stars
333
Forks
4
Bundled files
251
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 251 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mizchi on GitHub. Read the source before you install it.

Installation

Install the Cloudflare Deploy AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mizchi/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/cloudflare-deploy .claude/skills/cloudflare-deploy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cloudflare Deploy in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cloudflare Deploy on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cloudflare Deploy is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cloudflare Deploy

Consolidated skill for building on the Cloudflare platform. Use decision trees below to find the right product, then load detailed references.

Prerequisites

  • When sandboxing blocks the deployment network calls, rerun with sandbox_permissions=require_escalated.
  • The deployment might take a few minutes. Use appropriate timeout values.

Authentication (Required Before Deploy)

Verify auth before wrangler deploy, wrangler pages deploy, or npm run deploy:

bash
npx wrangler whoami    # Shows account if authenticated

Not authenticated? → references/wrangler/auth.md

  • Interactive/local: wrangler login (one-time OAuth)
  • CI/CD: Set CLOUDFLARE_API_TOKEN env var

When to Read references/

This SKILL.md is an index + decision tree. Actual implementation details (wrangler.jsonc binding syntax, SDK-specific APIs, product gotchas) live under references/<product>/.

Rules of thumb:

  • Picking a product? Use decision trees below, then load references/<picked-product>/
  • Writing a new wrangler.jsonc? Always references/workers/configuration.md first (binding shapes are non-inheritable and easy to get wrong)
  • CI/CD setup? Load references/ci/github-actions.md (GitHub Actions + OIDC + PR preview + tag deploy recipes)
  • Deploy fails / unexpected error? Grep references/<product>/gotchas.md before re-running
  • The minimal example below covers Workers + KV + secret — for anything beyond that, descend into references

Minimal Worker Example (copy-paste starter)

For a Hello-world Worker with one KV binding and one secret, you don't need to read references/ at all:

jsonc
// wrangler.jsonc
{
  "$schema": "node_modules/wrangler/config-schema.json",
  "name": "my-worker",
  "main": "src/index.ts",
  "compatibility_date": "2026-09-01",   // use today's date for a new Worker
  "compatibility_flags": ["nodejs_compat"],
  "observability": { "enabled": true },
  "kv_namespaces": [
    { "binding": "CACHE", "id": "<replace-with-kv-id>" }
  ]
}
ts
// src/index.ts
export interface Env {
  CACHE: KVNamespace;
  API_SECRET: string;
}
export default {
  async fetch(req: Request, env: Env): Promise<Response> {
    const hit = await env.CACHE.get("greeting");
    return new Response(hit ?? "hello");
  }
};

Bootstrap commands:

bash
npx wrangler kv namespace create CACHE          # copy printed id into wrangler.jsonc
npx wrangler secret put API_SECRET              # paste value interactively
npx wrangler types                              # generate Env types (optional)
npx wrangler dev                                # local dev at localhost:8787
npx wrangler deploy                             # production deploy

Pick compatibility_date = today's date (YYYY-MM-DD). Update when upgrading wrangler.

For Pages / D1 / Durable Objects / multi-env / CI — descend into references/.

Quick Decision Trees

"I need to run code"

Need to run code?
├─ Serverless functions at the edge → workers/
├─ Full-stack web app with Git deploys → pages/
├─ Stateful coordination/real-time → durable-objects/
├─ Long-running multi-step jobs → workflows/
├─ Run containers → containers/
├─ Multi-tenant (customers deploy code) → workers-for-platforms/
├─ Scheduled tasks (cron) → cron-triggers/
├─ Lightweight edge logic (modify HTTP) → snippets/
├─ Process Worker execution events (logs/observability) → tail-workers/
└─ Optimize latency to backend infrastructure → smart-placement/

"I need to store data"

Need storage?
├─ Key-value (config, sessions, cache) → kv/
├─ Relational SQL → d1/ (SQLite) or hyperdrive/ (existing Postgres/MySQL)
├─ Object/file storage (S3-compatible) → r2/
├─ Message queue (async processing) → queues/
├─ Vector embeddings (AI/semantic search) → vectorize/
├─ Strongly-consistent per-entity state → durable-objects/ (DO storage)
├─ Secrets management → secrets-store/
├─ Streaming ETL to R2 → pipelines/
└─ Persistent cache (long-term retention) → cache-reserve/

"I need AI/ML"

Need AI?
├─ Run inference (LLMs, embeddings, images) → workers-ai/
├─ Vector database for RAG/search → vectorize/
├─ Build stateful AI agents → agents-sdk/
├─ Gateway for any AI provider (caching, routing) → ai-gateway/
└─ AI-powered search widget → ai-search/

"I need networking/connectivity"

Need networking?
├─ Expose local service to internet → tunnel/
├─ TCP/UDP proxy (non-HTTP) → spectrum/
├─ WebRTC TURN server → turn/
├─ Private network connectivity → network-interconnect/
├─ Optimize routing → argo-smart-routing/
├─ Optimize latency to backend (not user) → smart-placement/
└─ Real-time video/audio → realtimekit/ or realtime-sfu/

"I need security"

Need security?
├─ Web Application Firewall → waf/
├─ DDoS protection → ddos/
├─ Bot detection/management → bot-management/
├─ API protection → api-shield/
├─ CAPTCHA alternative → turnstile/
└─ Credential leak detection → waf/ (managed ruleset)

"I need media/content"

Need media?
├─ Image optimization/transformation → images/
├─ Video streaming/encoding → stream/
├─ Browser automation/screenshots → browser-rendering/
└─ Third-party script management → zaraz/

"I need infrastructure-as-code"

Need IaC? → pulumi/ (Pulumi), terraform/ (Terraform), or api/ (REST API)

Product Index

Compute & Runtime

ProductReference
Workersreferences/workers/
Pagesreferences/pages/
Pages Functionsreferences/pages-functions/
Durable Objectsreferences/durable-objects/
Workflowsreferences/workflows/
Containersreferences/containers/
Workers for Platformsreferences/workers-for-platforms/
Cron Triggersreferences/cron-triggers/
Tail Workersreferences/tail-workers/
Snippetsreferences/snippets/
Smart Placementreferences/smart-placement/

Storage & Data

ProductReference
KVreferences/kv/
D1references/d1/
R2references/r2/
Queuesreferences/queues/
Hyperdrivereferences/hyperdrive/
DO Storagereferences/do-storage/
Secrets Storereferences/secrets-store/
Pipelinesreferences/pipelines/
R2 Data Catalogreferences/r2-data-catalog/
R2 SQLreferences/r2-sql/

AI & Machine Learning

ProductReference
Workers AIreferences/workers-ai/
Vectorizereferences/vectorize/
Agents SDKreferences/agents-sdk/
AI Gatewayreferences/ai-gateway/
AI Searchreferences/ai-search/

Networking & Connectivity

ProductReference
Tunnelreferences/tunnel/
Spectrumreferences/spectrum/
TURNreferences/turn/
Network Interconnectreferences/network-interconnect/
Argo Smart Routingreferences/argo-smart-routing/
Workers VPCreferences/workers-vpc/

Security

ProductReference
WAFreferences/waf/
DDoS Protectionreferences/ddos/
Bot Managementreferences/bot-management/
API Shieldreferences/api-shield/
Turnstilereferences/turnstile/

Media & Content

ProductReference
Imagesreferences/images/
Streamreferences/stream/
Browser Renderingreferences/browser-rendering/
Zarazreferences/zaraz/

Real-Time Communication

ProductReference
RealtimeKitreferences/realtimekit/
Realtime SFUreferences/realtime-sfu/

Developer Tools

ProductReference
Wranglerreferences/wrangler/
Miniflarereferences/miniflare/
C3references/c3/
Observabilityreferences/observability/
Analytics Enginereferences/analytics-engine/
Web Analyticsreferences/web-analytics/
Sandboxreferences/sandbox/
Workerdreferences/workerd/
Workers Playgroundreferences/workers-playground/

Infrastructure as Code

ProductReference
Pulumireferences/pulumi/
Terraformreferences/terraform/
APIreferences/api/

Other Services

ProductReference
Email Routingreferences/email-routing/
Email Workersreferences/email-workers/
Static Assetsreferences/static-assets/
Bindingsreferences/bindings/
Cache Reservereferences/cache-reserve/

Troubleshooting

Escalated Network Access

If deployment fails due to network issues (timeouts, DNS errors, connection resets), rerun the deploy with escalated permissions (use sandbox_permissions=require_escalated). The deploy requires escalated network access when sandbox networking blocks outbound requests.

Example guidance to the user:

The deploy needs escalated network access to deploy to Cloudflare. I can rerun the command with escalated permissions—want me to proceed?

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 140 more files.

Frequently asked questions

What does the Cloudflare Deploy AI skill do?

Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.

Why use Cloudflare Deploy on TypingMind?

Because you install it once and use it with any model. Cloudflare Deploy is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cloudflare Deploy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mizchi/skills/tree/main/cloudflare-deploy. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cloudflare Deploy?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cloudflare Deploy?

As many as you like. As long as a model supports skills, you can use Cloudflare Deploy with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cloudflare Deploy AI skill free?

It is published on GitHub by mizchi. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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