martinholovsky/claude-skills-generator
Overview
This skill is an expert RabbitMQ administrator and developer focused on designing, operating, and optimizing message broker systems for production. I help design exchange patterns, tune throughput, implement high-availability clusters, and build reliable failure-handling and observability. The goal is predictable message delivery, secure deployments, and measurable performance under load.
How this skill works
I inspect architecture choices (exchanges, queues, bindings), broker configuration (memory, disk, policies), and client patterns (prefetch, confirms, batching). I evaluate HA options (quorum vs mirrored queues), DLX and retry strategies, and provide actionable tuning for throughput and latency. I also verify security posture (TLS, authz) and observability (metrics, alerts, management API).
When to use it
- Designing a new message-driven system or refactoring existing queues
- Troubleshooting message loss, ack/nack behavior, or DLX routing
- Optimizing throughput: prefetch, batching, confirms, and pooling
- Planning or operating RabbitMQ clusters and HA strategies
- Hardening broker security and auditability for production
Best practices
- Follow TDD for message flows: unit test consumers and integration test confirms/DLX
- Tune prefetch by consumer latency: high for fast consumers, low for slow ones
- Enable durability + publisher confirms to avoid silent message loss
- Use DLX, TTL, and retries to separate permanent and transient failures
- Prefer quorum queues for consistency, lazy queues for large disk-backed backlogs
- Instrument queues, consumer lag, and node health; alert on memory/disk thresholds
Example use cases
- Implement a pub/sub architecture with topic exchanges and consumer groups
- Migrate classic mirrored queues to quorum queues for safer failover
- Design DLX-based retry choreography and dead-letter monitoring
- Optimize a high-throughput publisher using batching and async confirms
- Set up connection pooling and consumer prefetch tuning to reduce resource churn
FAQ
Base it on average processing time: fast (<100ms) use 20–50, medium (100ms–1s) use 5–20, slow (>1s) use 1–5; validate with consumer utilization metrics.
When should I use lazy vs quorum queues?
Use lazy queues when backlog regularly exceeds memory and ordering is less critical. Use quorum queues when consistency and data safety across node failures are priorities.
38 skills
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