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

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/openai/cloudflare/download

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.

Source	How to retrieve	Use for
Cloudflare docs	Search `https://developers.cloudflare.com/` directly	Limits, pricing, API reference, compatibility dates/flags
Workers types	`npm pack @cloudflare/workers-types` or check `node_modules`	Type signatures, binding shapes, handler types
Wrangler config schema	`node_modules/wrangler/config-schema.json`	Config fields, binding shapes, allowed values
Product changelogs	`https://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

Product	Reference
Workers	`references/workers/`
Pages	`references/pages/`
Pages Functions	`references/pages-functions/`
Durable Objects	`references/durable-objects/`
Workflows	`references/workflows/`
Containers	`references/containers/`
Workers for Platforms	`references/workers-for-platforms/`
Cron Triggers	`references/cron-triggers/`
Tail Workers	`references/tail-workers/`
Snippets	`references/snippets/`
Smart Placement	`references/smart-placement/`

Storage & Data

Product	Reference
KV	`references/kv/`
D1	`references/d1/`
R2	`references/r2/`
Queues	`references/queues/`
Hyperdrive	`references/hyperdrive/`
DO Storage	`references/do-storage/`
Secrets Store	`references/secrets-store/`
Pipelines	`references/pipelines/`
R2 Data Catalog	`references/r2-data-catalog/`
R2 SQL	`references/r2-sql/`

AI & Machine Learning

Product	Reference
Workers AI	`references/workers-ai/`
Vectorize	`references/vectorize/`
Agents SDK	`references/agents-sdk/`
AI Gateway	`references/ai-gateway/`
AI Search	`references/ai-search/`

Networking & Connectivity

Product	Reference
Tunnel	`references/tunnel/`
Spectrum	`references/spectrum/`
TURN	`references/turn/`
Network Interconnect	`references/network-interconnect/`
Argo Smart Routing	`references/argo-smart-routing/`
Workers VPC	`references/workers-vpc/`

Security

Product	Reference
WAF	`references/waf/`
DDoS Protection	`references/ddos/`
Bot Management	`references/bot-management/`
API Shield	`references/api-shield/`
Turnstile	`references/turnstile/`

Media & Content

Product	Reference
Images	`references/images/`
Stream	`references/stream/`
Browser Rendering	`references/browser-rendering/`
Zaraz	`references/zaraz/`

Real-Time Communication

Product	Reference
RealtimeKit	`references/realtimekit/`
Realtime SFU	`references/realtime-sfu/`

Developer Tools

Product	Reference
Wrangler	`references/wrangler/`
Miniflare	`references/miniflare/`
C3	`references/c3/`
Observability	`references/observability/`
GraphQL Analytics API	`references/graphql-api/`
Analytics Engine	`references/analytics-engine/`
Web Analytics	`references/web-analytics/`
Sandbox	`references/sandbox/`
Workerd	`references/workerd/`
Workers Playground	`references/workers-playground/`

Infrastructure as Code

Product	Reference
Pulumi	`references/pulumi/`
Terraform	`references/terraform/`
API	`references/api/`

Other Services

Product	Reference
Email Routing	`references/email-routing/`
Email Workers	`references/email-workers/`
Static Assets	`references/static-assets/`
Bindings	`references/bindings/`
Cache Reserve	`references/cache-reserve/`

Files

ATTRIBUTION.mdAdded by AutoGineer906 B
LICENSE.txt10.5 KiB
SKILL.md8.0 KiB
agents/openai.yaml375 B
assets/cloudflare-small.svg1.2 KiB
assets/cloudflare.png1.2 KiB
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references/vectorize/README.md

Cloudflare Vectorize

Globally distributed vector database for AI applications. Store and query vector embeddings for semantic search, recommendations, RAG, and classification.

Status: Generally Available (GA) | Last Updated: 2026-01-27

Quick Start

// 1. Create index
// npx wrangler vectorize create my-index --dimensions=768 --metric=cosine

// 2. Configure binding (wrangler.jsonc)
// { "vectorize": [{ "binding": "VECTORIZE", "index_name": "my-index" }] }

// 3. Query vectors
const matches = await env.VECTORIZE.query(queryVector, { topK: 5 });

Key Features

10M vectors per index (V2)
Dimensions up to 1536 (32-bit float)
Three distance metrics: cosine, euclidean, dot-product
Metadata filtering (up to 10 indexes)
Namespace support (50K namespaces paid, 1K free)
Seamless Workers AI integration
Global distribution

Reading Order

Task	Files to Read
New to Vectorize	README only
Implement feature	README + api + patterns
Setup/configure	README + configuration
Debug issues	gotchas
Integrate with AI	README + patterns
RAG implementation	README + patterns

File Guide

README.md (this file): Overview, quick decisions
api.md: Runtime API, types, operations (query/insert/upsert)
configuration.md: Setup, CLI, metadata indexes
patterns.md: RAG, Workers AI, OpenAI, LangChain, multi-tenant
gotchas.md: Limits, pitfalls, troubleshooting

Distance Metric Selection

Choose based on your use case:

What are you building?
├─ Text/semantic search → cosine (most common)
├─ Image similarity → euclidean
├─ Recommendation system → dot-product
└─ Pre-normalized vectors → dot-product

Metric	Best For	Score Interpretation
`cosine`	Text embeddings, semantic similarity	Higher = closer (1.0 = identical)
`euclidean`	Absolute distance, spatial data	Lower = closer (0.0 = identical)
`dot-product`	Recommendations, normalized vectors	Higher = closer

Note: Index configuration is immutable. Cannot change dimensions or metric after creation.

Multi-Tenancy Strategy

How many tenants?
├─ < 50K tenants → Use namespaces (recommended)
│   ├─ Fastest (filter before vector search)
│   └─ Strict isolation
├─ > 50K tenants → Use metadata filtering
│   ├─ Slower (post-filter after vector search)
│   └─ Requires metadata index
└─ Per-tenant indexes → Only if compliance mandated
    └─ 50K index limit per account (paid plan)

Common Workflows

Semantic Search

// 1. Generate embedding
const result = await env.AI.run("@cf/baai/bge-base-en-v1.5", { text: [query] });

// 2. Query Vectorize
const matches = await env.VECTORIZE.query(result.data[0], {
  topK: 5,
  returnMetadata: "indexed"
});

RAG Pattern

// 1. Generate query embedding
const embedding = await env.AI.run("@cf/baai/bge-base-en-v1.5", { text: [query] });

// 2. Search Vectorize
const matches = await env.VECTORIZE.query(embedding.data[0], { topK: 5 });

// 3. Fetch full documents from R2/D1/KV
const docs = await Promise.all(matches.matches.map(m =>
  env.R2.get(m.metadata.key).then(obj => obj?.text())
));

// 4. Generate LLM response with context
const answer = await env.AI.run("@cf/meta/llama-3-8b-instruct", {
  prompt: `Context: ${docs.join("\n\n")}\n\nQuestion: ${query}\n\nAnswer:`
});

Critical Gotchas

See gotchas.md for details. Most important:

Async mutations: Inserts take 5-10s to be queryable
500 batch limit: Workers API enforces 500 vectors per call (undocumented)
Metadata truncation: "indexed" returns first 64 bytes only
topK with metadata: Max 20 (not 100) when using returnValues or returnMetadata: "all"
Metadata indexes first: Must create before inserting vectors

Resources

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

2026-11-08

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

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by Cloudflare

Cloudflare Platform Skill

Retrieval Sources

Quick Decision Trees

"I need to run code"

"I need to store data"

"I need AI/ML"

"I need networking/connectivity"

"I need security"

"I need media/content"

"I need analytics/metrics data"

"I need infrastructure-as-code"

Product Index

Compute & Runtime

Storage & Data

AI & Machine Learning

Networking & Connectivity

Security

Media & Content

Real-Time Communication

Developer Tools

Infrastructure as Code

Other Services

Files

references/vectorize/README.md

Cloudflare Vectorize

Quick Start

Key Features

Reading Order

File Guide

Distance Metric Selection

Multi-Tenancy Strategy

Common Workflows

Semantic Search

RAG Pattern

Critical Gotchas

Resources

Requirements and compatibility

Security

Attribution and licence

Related skills

Modal

Cloud Infrastructure Network Engineer

Deployment Validation Cloud Architect

Airflow Dag Patterns

Cost Optimization

Hybrid Cloud Networking

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