quality-perf-review

Identify performance bottlenecks by running static and dynamic analysis on your codebase to detect N+1 database queries, event-loop blocking operations, and frontend bundle bloat. This systematic evaluation measures runtime metrics to ensure evidence-based optimization.

Audit full-stack performance by scanning code for anti-patterns and executing permission-based dynamic profiling under load. This evidence-based approach validates findings before suggesting safe, non-breaking optimizations to improve responsiveness.

Static analysis finds N+1 database queries and bundle bloat by scanning the full-stack codebase for common performance anti-patterns like blocking I/O. It evaluates code patterns systematically to pinpoint slow paths without executing the application.

You can use dynamic profiling to measure real-world performance under load through guided, permission-based benchmarking. This dynamic analysis targets backend database queries and event-loop blocking operations to capture runtime metrics.

The performance review process validates optimization suggestions through an interactive, step-by-step workflow. It confirms findings with the user before applying safe, non-breaking optimizations to remediate slow code paths.

Avoid micro-optimizations when performance degradation requires evidence-based remediation of full-stack bottlenecks. Instead, systematically evaluate code patterns and runtime metrics to target actual database queries and event-loop blocking operations.