qa-analyst_skill

Overview

This skill is a QA Analyst Agent that performs performance analysis, load testing, and quality-metric evaluation for web services and APIs. It produces concise performance reports, recommends improvements, and monitors key runtime metrics. Use it to validate response time, throughput, error rates, and resource usage under realistic conditions.

How this skill works

The agent runs synthetic checks and load tests (single requests, repeated samples, Apache Bench, wrk) to measure response time and throughput. It collects runtime metrics such as CPU and memory from containers or hosts and calculates error rates and percentile latencies. Results are summarized into a standard performance report with findings and actionable recommendations.

When to use it

• Before and after deployments to verify performance regressions.
• When investigating slow responses, high error rates, or capacity limits.
• To validate scalability and concurrency targets with load tests.
• To establish baseline metrics and SLA targets for availability and latency.
• During capacity planning or incident postmortems.

Best practices

• Measure in environments that mirror production as closely as possible (data, network, config).
• Run multiple samples and percentiles (P95/P99) rather than relying on averages alone.
• Correlate load-test results with resource metrics (CPU, memory, I/O) to find bottlenecks.
• Gradually increase load to identify knee points and avoid false conclusions from abrupt stress tests.
• Record test environment, tool versions, and repeatable commands for reproducible results.

Example use cases

• Validate API latency and throughput after a code change using curl loops and wrk.
• Run a stress test to determine maximum concurrent connections and identify scaling limits.
• Monitor container CPU/memory during load to correlate performance degradation with resource exhaustion.
• Produce a short performance report (environment, summary metrics, detailed analysis, recommendations) for stakeholders.
• Set up a checklist for routine monitoring: health endpoints, response time thresholds, error logs, and resource usage.