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Cloudflare

OpenAIOfficialCreated by CloudflareDistributed by OpenAI

  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
  • Medium risk

From the author

Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
— the description by Cloudflare

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Cloudflare platform skill provides a centralized resource for developers building on Cloudflare's edge network. It covers the full ecosystem, including compute (Workers, Pages), storage (KV, D1, R2), AI integration (Workers AI, Agents SDK), networking, and security. The skill emphasizes a retrieval-first approach, directing users to official Cloudflare documentation and configuration schemas to ensure accuracy regarding API signatures, limits, and pricing.

What it does

  • Provides decision trees to help select the right Cloudflare product for specific compute, storage, or networking needs.
  • Offers structured references for the Cloudflare Agents SDK, including lifecycle hooks and state management.
  • Guides users on integrating AI models and vector databases into edge applications.
  • Outlines methods for managing infrastructure-as-code using Terraform or Pulumi.
  • Facilitates access to product-specific documentation for security, media, and analytics services.
  • Maintains a directory of developer tools like Wrangler and Miniflare for local development and testing.

When to use it

  • When starting a new project on the Cloudflare platform and needing to choose the appropriate architecture.
  • When implementing stateful AI agents using the Cloudflare Agents SDK.
  • When configuring edge compute, storage bindings, or networking rules.
  • When troubleshooting API limits, configuration errors, or deployment issues.
  • When integrating AI models or vector search into existing edge applications.

Advantages

  • Consolidates a vast ecosystem into a navigable, task-oriented structure.
  • Promotes the use of official, up-to-date documentation over potentially stale training data.
  • Simplifies complex architectural decisions through clear, logic-based decision trees.
  • Provides specific code patterns for advanced features like Durable Objects and AI agents.
  • Supports modern infrastructure-as-code workflows for consistent deployments.

Usage examples

“I need to build a stateful AI chat agent on Cloudflare. How do I start?”
The agent will guide you to use the AIChatAgent class from the Agents SDK, explain how to manage message history, and provide a template for integrating AI models.
“Which storage solution should I use for relational data in my Worker?”
The agent will point you to D1 for SQLite-based relational storage or Hyperdrive for connecting to existing Postgres/MySQL databases.
“How do I expose my local development server to the internet via Cloudflare?”
The agent will provide instructions on using Cloudflare Tunnel to securely connect your local service to the Cloudflare edge.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/openai/cloudflare/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip cloudflare.zip -d .agents/skills

Documentation by Cloudflare

Cloudflare Platform Skill

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

Your knowledge of Cloudflare APIs, types, limits, and pricing may be outdated. Prefer retrieval over pre-training — the references in this skill are starting points, not source of truth.

Retrieval Sources

Fetch the latest information before citing specific numbers, API signatures, or configuration options. Do not rely on baked-in knowledge or these reference files alone.

SourceHow to retrieveUse for
Cloudflare docsSearch https://developers.cloudflare.com/ directlyLimits, pricing, API reference, compatibility dates/flags
Workers typesnpm pack @cloudflare/workers-types or check node_modulesType signatures, binding shapes, handler types
Wrangler config schemanode_modules/wrangler/config-schema.jsonConfig fields, binding shapes, allowed values
Product changelogshttps://developers.cloudflare.com/changelog/Recent changes to limits, features, deprecations

When a reference file and the docs disagree, trust the docs. This is especially important for: numeric limits, pricing tiers, type signatures, and configuration options.

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 analytics/metrics data"
Need analytics?
├─ Query across all Cloudflare products (HTTP, Workers, DNS, etc.) → graphql-api/
├─ Custom high-cardinality metrics from Workers → analytics-engine/
├─ Client-side (RUM) performance data → web-analytics/
├─ Workers Logs and real-time debugging → observability/
└─ Raw logs (Logpush to external tools) → Cloudflare docs
"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/
GraphQL Analytics APIreferences/graphql-api/
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/

Files

references/smart-placement/patterns.md

Smart Placement Patterns

Backend Worker with Database Access

export default {
  async fetch(request: Request, env: Env): Promise<Response> {
    const user = await env.DATABASE.prepare('SELECT * FROM users WHERE id = ?').bind(userId).first();
    const orders = await env.DATABASE.prepare('SELECT * FROM orders WHERE user_id = ?').bind(userId).all();
    return Response.json({ user, orders });
  }
};
{ "placement": { "mode": "smart" }, "d1_databases": [{ "binding": "DATABASE", "database_id": "xxx" }] }

Frontend + Backend Split (Service Bindings)

Frontend: Runs at edge for fast user response Backend: Smart Placement runs close to database

// Frontend Worker - routes requests to backend
interface Env {
  BACKEND: Fetcher;  // Service Binding to backend Worker
}

export default {
  async fetch(request: Request, env: Env): Promise<Response> {
    if (new URL(request.url).pathname.startsWith('/api/')) {
      return env.BACKEND.fetch(request);  // Forward to backend
    }
    return new Response('Frontend content');
  }
};

// Backend Worker - database operations
interface BackendEnv {
  DATABASE: D1Database;
}

export default {
  async fetch(request: Request, env: BackendEnv): Promise<Response> {
    const data = await env.DATABASE.prepare('SELECT * FROM table').all();
    return Response.json(data);
  }
};

CRITICAL: Use fetch-based Service Bindings (shown above). If using RPC with WorkerEntrypoint, Smart Placement will NOT optimize those method calls - only fetch handlers are affected.

RPC vs Fetch - CRITICAL: Smart Placement ONLY works with fetch-based bindings, NOT RPC.

// ❌ RPC - Smart Placement has NO EFFECT on backend RPC methods
export class BackendRPC extends WorkerEntrypoint {
  async getData() {
    // ALWAYS runs at edge, Smart Placement ignored
    return await this.env.DATABASE.prepare('SELECT * FROM table').all();
  }
}

// ✅ Fetch - Smart Placement WORKS
export default {
  async fetch(request: Request, env: Env): Promise<Response> {
    // Runs close to DATABASE when Smart Placement enabled
    const data = await env.DATABASE.prepare('SELECT * FROM table').all();
    return Response.json(data);
  }
};

External API Integration

export default {
  async fetch(request: Request, env: Env): Promise<Response> {
    const apiUrl = 'https://api.partner.com';
    const headers = { 'Authorization': `Bearer ${env.API_KEY}` };

    const [profile, transactions] = await Promise.all([
      fetch(`${apiUrl}/profile`, { headers }),
      fetch(`${apiUrl}/transactions`, { headers })
    ]);

    return Response.json({
      profile: await profile.json(),
      transactions: await transactions.json()
    });
  }
};

SSR / API Gateway Pattern

// Frontend (edge) - auth/routing close to user
export default {
  async fetch(request: Request, env: Env) {
    if (!request.headers.get('Authorization')) {
      return new Response('Unauthorized', { status: 401 });
    }
    const data = await env.BACKEND.fetch(request);
    return new Response(renderPage(await data.json()), {
      headers: { 'Content-Type': 'text/html' }
    });
  }
};

// Backend (Smart Placement) - DB operations close to data
export default {
  async fetch(request: Request, env: Env) {
    const data = await env.DATABASE.prepare('SELECT * FROM pages WHERE id = ?').bind(pageId).first();
    return Response.json(data);
  }
};

Durable Objects with Smart Placement

Key principle: Smart Placement does NOT control WHERE Durable Objects run. DOs always run in their designated region (based on jurisdiction or smart location hints).

What Smart Placement DOES affect: The location of the coordinator Worker's fetch handler that makes calls to multiple DOs.

Pattern: Enable Smart Placement on coordinator Worker that aggregates data from multiple DOs:

// Worker with Smart Placement - aggregates data from multiple DOs
export default {
  async fetch(request: Request, env: Env): Promise<Response> {
    const userId = new URL(request.url).searchParams.get('user');

    // Get DO stubs
    const userDO = env.USER_DO.get(env.USER_DO.idFromName(userId));
    const analyticsID = env.ANALYTICS_DO.idFromName(`analytics-${userId}`);
    const analyticsDO = env.ANALYTICS_DO.get(analyticsID);

    // Fetch from multiple DOs
    const [userData, analyticsData] = await Promise.all([
      userDO.fetch(new Request('https://do/profile')),
      analyticsDO.fetch(new Request('https://do/stats'))
    ]);

    return Response.json({
      user: await userData.json(),
      analytics: await analyticsData.json()
    });
  }
};
// wrangler.jsonc
{
  "placement": { "mode": "smart" },
  "durable_objects": {
    "bindings": [
      { "name": "USER_DO", "class_name": "UserDO" },
      { "name": "ANALYTICS_DO", "class_name": "AnalyticsDO" }
    ]
  }
}

When this helps:

  • Worker's fetch handler runs closer to DO regions, reducing network latency for multiple DO calls

  • Most beneficial when DOs are geographically concentrated or in specific jurisdictions

  • Helps when coordinator makes many sequential or parallel DO calls

When this DOESN'T help:

  • DOs are globally distributed (no single optimal Worker location)

  • Worker only calls a single DO

  • DO calls are infrequent or cached

Best Practices

  • Split full-stack apps: frontend at edge, backend with Smart Placement

  • Use fetch-based Service Bindings (not RPC)

  • Enable for backend logic: APIs, data aggregation, DB operations

  • Don't enable for: static content, edge logic, RPC methods, Pages with run_worker_first

  • Wait 15+ min for analysis, verify placement_status = SUCCESS

Requirements and compatibility

Written for: OpenAI Codex

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

What our scanner noticed· Medium risk

  • Possible data-exfiltration endpoints
  • Instructions that use the network
  • Downloads piped into a shell

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Cloudflare
Publisher
OpenAI (Official)
Distributed by
OpenAI
Source
openai/plugins · plugins/cloudflare/skills/cloudflare · commit d420d13
Licence
Apache License 2.0 (redistribution allowed)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Cloudflare or OpenAI.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download cloudflare.zip