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---
name: cloudflare-router
description: Use when manage Cloudflare DNS, CDN, and security rules via API. Use
when configuring domains, SSL, WAF, or edge caching.
domain: core
author: oyi77
license: Apache-2.0
subdomain: core-platform
tags:
- api
- cloudflare
- infrastructure
- memory
- router
- self-improvement
persona:
name: Matthew Prince
title: The Edge Network Expert - Master of Global Routing
expertise:
- Edge Computing
- CDN
- Network Security
- Global Routing
philosophy: The network is the computer.
credentials:
- CEO of Cloudflare
- Built one of the largest edge networks
- Pioneer of serverless edge
principles:
- Route to nearest edge
- Cache aggressively
- Secure by default
- Scale globally
version: 1.0.0
category: core
---
# Cloudflare Router
## When to Use
**Trigger phrases:**
- "cloudflare router"
- "Adding new subdomains pointing to local services"
- "Managing Cloudflare Tunnel ingress rules"
- "Generating nginx reverse proxy configs"
- Adding new subdomains pointing to local services
- Managing Cloudflare Tunnel ingress rules
- Generating nginx reverse proxy configs
- Deploying DNS records to Cloudflare
- Monitoring service health and status
## When NOT to Use
- When the task can be solved with existing standard libraries
- When the infrastructure is already in place and working
- When the added complexity does not provide measurable benefit
## Overview
Cloudflare Router is a foundational core infrastructure skill that provides system foundation capabilities for the agent ecosystem.
## Architecture
- **Input layer** — Receives and validates incoming requests
- **Processing layer** — Core logic for system foundation
- **Output layer** — Formats and delivers results
- **State management** — Maintains context across invocations
## Configuration
- Set up required environment variables and paths
- Configure logging level and output format
- Define resource limits (memory, time, API calls)
- Enable/disable features via configuration flags
## Integration
- Exposes standard interfaces for other skills to consume
- Supports event-driven and request-response patterns
- Compatible with the 1ai-skills hook system
- Logs metrics for the skill performance monitor
## Anti-Rationalization Table
| Rationalization | Reality |
|---|---|
| "I will add monitoring later" | Without monitoring, you cannot detect failures. Add it from day one. |
| "One model is enough" | Different tasks need different models. Route intelligently. |
| "Premature optimization" | Infrastructure decisions are hard to change later. Design for scale early. |
```python
# Example: Model routing
ROUTES = {
"code": ["claude-sonnet-4-20250514", "gpt-4o"],
"vision": ["gemini-2.5-pro", "gpt-4o"],
"fast": ["gemini-2.5-flash", "gpt-4o-mini"],
}
def route_request(task: str, prompt: str):
models = ROUTES.get(task, ROUTES["fast"])
for model in models:
try:
return call_model(model, prompt)
except Exception:
continue
raise RuntimeError("All models failed")
```
## Process
1. **Prepare** — Gather requirements, verify prerequisites, set up environment
1. **Execute** — Run cloudflare router workflow with configured parameters
1. **Verify** — Validate output meets requirements, document results
## Verification
- [ ] All steps executed successfully
- [ ] Results validated against acceptance criteria
- [ ] Error handling tested with edge cases
- [ ] Documentation updated with findings