openclaw-test-performance

Benchmarking OpenClaw test suite performance involves collecting wall time, Vitest duration, import duration, max RSS, CPU usage, and heap snapshots to identify runtime bottlenecks and memory hotspots.

High memory usage and slow execution in OpenClaw test suites are often caused by full bundled channel runtime loading, improper API method usage, and SDK barrel pulling. Diagnosing these root causes requires analyzing CPU and RSS heap growth metrics.

Yes, profiling OpenClaw plugin performance requires Vitest, Crabbox, and specific OpenClaw configurations to capture CPU and memory profiling metrics. These dependencies enable the collection of heap snapshots and import durations.

The best way to optimize slow OpenClaw test runs is through code refactoring, dependency injection, and reusing suite-level servers and clients. These steps reduce full bundled runtime loading and minimize heap growth during execution.

Yes, you can diagnose heap growth and CPU bottlenecks in OpenClaw plugin suites by analyzing heap snapshots and max RSS metrics. The skill identifies slow coverage paths and improper API methods causing high resource consumption.

Limitations when tuning OpenClaw test performance include the strict requirement for specific OpenClaw configurations alongside Vitest and Crabbox. Without these exact dependencies, the memory and CPU profiling capabilities cannot function properly.