openrouter-performance-tuning skill

Overview

This skill helps optimize OpenRouter deployments for lower latency and higher throughput. It documents practical techniques like connection pooling, asynchronous request handling, and caching to reduce response times and improve resource utilization. The guidance is implementation-focused so you can apply changes, measure impact, and iterate quickly.

How this skill works

The skill inspects request/response patterns and suggests code and configuration changes to reduce latency and increase concurrency. It guides you through adding connection pooling, converting blocking calls to async, introducing result caching, and validating improvements with baseline measurements and monitoring. It also recommends production safeguards such as timeouts, retries, and observability hooks.

When to use it

• When average or tail latency to OpenRouter exceeds your SLA
• When throughput is limited under expected concurrency
• Before scaling infrastructure to identify software bottlenecks
• When integrating OpenRouter into latency-sensitive user flows
• During performance regression testing after upgrades

Best practices

• Measure a clear baseline (p95, p99, throughput) before changes
• Use connection pooling and keepalive to avoid TCP/SSL overhead
• Prefer async/non-blocking calls in high-concurrency paths
• Cache deterministic or repeated responses with TTL and invalidation
• Instrument latency, error rates, and queue lengths for feedback

Example use cases

• Reduce API latency for a chat frontend by switching to async HTTP clients and pooling
• Increase throughput for batch inference jobs by parallelizing requests with controlled concurrency
• Lower costs by caching repeated model outputs that are business-safe to reuse
• Prevent service disruption by adding circuit breakers, short timeouts, and retry backoff
• Validate upgrade impact by running A/B performance tests against the baseline

FAQ