Does it support explicit message acknowledgement?

Yes, the skill provides templates for explicit ack() to ensure non-idempotent operations like database writes are handled reliably without accidental retries.

Can I use this skill to optimize queue throughput?

Absolutely. It includes a queue-optimizer agent and batching patterns to help you scale your processing up to the limit of 5,000 messages per second.

Does this skill help with Dead Letter Queues (DLQ)?

Yes, it includes specific templates and rules for configuring DLQs to capture and troubleshoot permanently failed messages in production environments.

How do I handle messages larger than 128KB in Cloudflare Queues?

The skill provides a pattern to store large payloads in R2 and send the reference key through the queue, effectively bypassing the 128KB message size limit.

Cloudflare Queues

Name: Cloudflare Queues
Author: secondsky

bysecondsky

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Cloud Infrastructure

Configures and optimizes Cloudflare Queues for robust message processing, background jobs, and asynchronous worker communication.

About

This skill provides production-ready guidance for implementing Cloudflare Queues within the Workers ecosystem. It automates the setup of producers and consumers, implements critical error handling patterns like Dead Letter Queues (DLQ) and exponential backoff, and provides diagnostic tools to optimize throughput and message delivery. It is essential for developers building scalable, resilient serverless architectures that require asynchronous processing and reliable job scheduling with guaranteed delivery patterns.

Key Features

Support for large message handling via R2 storage integration
Advanced error handling patterns including DLQ and exponential backoff
21 GitHub stars
Interactive diagnostic agents for debugging and performance tuning
Automated setup of producers and consumers with best-practice configurations
Optimized batch processing for high-throughput messaging up to 5,000 msg/s

Use Cases

Non-idempotent database writes requiring explicit message acknowledgement
High-concurrency systems needing rate-limiting and retry logic
Asynchronous background tasks such as email notifications and image processing

About

Key Features

Support for large message handling via R2 storage integration
Advanced error handling patterns including DLQ and exponential backoff
21 GitHub stars
Interactive diagnostic agents for debugging and performance tuning
Automated setup of producers and consumers with best-practice configurations
Optimized batch processing for high-throughput messaging up to 5,000 msg/s

Use Cases

Non-idempotent database writes requiring explicit message acknowledgement
High-concurrency systems needing rate-limiting and retry logic
Asynchronous background tasks such as email notifications and image processing