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name: performance-benchmark description: | Comprehensive performance testing framework for load testing, stress testing, and benchmarking. Measures throughput, latency percentiles (p50, p95, p99), and resource utilization. Identifies bottlenecks and detects performance regressions across releases. license: MIT allowed-tools:

• Bash
• Read
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• Grep
• WebFetch compatibility: claude-code: ">=1.0.0" metadata: version: "1.0.0" author: "QuantQuiver AI R&D" category: "testing" tags:
  • performance
  • load-testing
  • stress-testing
  • benchmarking
  • latency

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Performance Benchmark Suite

Purpose

Comprehensive performance testing framework for load testing, stress testing, and benchmarking. Measures throughput, latency percentiles, and resource utilization. Identifies bottlenecks and detects performance regressions.

Triggers

Use this skill when:

• "load test"
• "benchmark"
• "performance test"
• "stress test"
• "profile this code"
• "find performance bottlenecks"
• "measure latency"
• "check for performance regression"

When to Use

• Pre-production performance validation
• Capacity planning
• SLA verification
• Release comparison
• Cost optimization
• Latency-sensitive applications

When NOT to Use

• Functional testing (use unit-test-generator)
• Security testing (use security-test-suite)
• Data quality validation (use data-validation)

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Core Instructions

Performance Test Types

Metrics Collected

Test Scenarios

Copyscenarios:
  baseline:
    rps: 100
    duration: 300s

  load_test:
    stages:
      - duration: 60s
        target_rps: 100
      - duration: 300s
        target_rps: 500
      - duration: 60s
        target_rps: 100

  stress_test:
    start_rps: 100
    step_rps: 50
    step_duration: 60s
    stop_on_error_rate: 5.0

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Templates

Performance Report

Copy# Performance Benchmark Report

**Target:** {target_url}
**Generated:** {timestamp}

## Executive Summary

| Metric | Value |
| ------ | ----- |
| Total Requests | {total_requests} |
| Best Throughput | {best_rps} RPS |
| Worst p99 Latency | {worst_p99}ms |

## {test_name}

**Duration:** {duration}s
**Throughput:** {rps} RPS
**Error Rate:** {error_rate}%

### Latency Distribution

| Percentile | Latency (ms) |
| ---------- | ------------ |
| p50 | {p50} |
| p95 | {p95} |
| p99 | {p99} |
| Max | {max} |

### Threshold Violations

- {violation_description}

## Recommendations

- {recommendation}

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Example

Input: Load test REST API endpoint

Output:

Copy## Executive Summary

**Overall Status:** PASSED

| Metric | Value |
| ------ | ----- |
| Total Requests | 45,230 |
| Best Throughput | 523.4 RPS |
| Worst p99 Latency | 187.3ms |

## Baseline Test

**Throughput:** 100.0 RPS
**Error Rate:** 0.03%

### Latency Distribution

| Percentile | Latency (ms) |
| ---------- | ------------ |
| p50 | 23.4 |
| p95 | 67.8 |
| p99 | 98.2 |

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Validation Checklist

• System under test is isolated
• Warmup period completed before measurement
• Sufficient test duration for statistical significance
• Resource monitoring data collected
• Baseline comparison performed (if available)
• All threshold violations documented
• Recommendations actionable and specific

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Related Skills

• unit-test-generator - For function-level testing
• api-contract-validator - For API correctness
• test-health-monitor - For tracking performance trends