analyze-code-quality
AgentAdvanced code quality analysis agent for comprehensive code reviews and improvements
Comprehensive performance benchmarking, regression detection and performance validation
Claude Code
> /plugin marketplace add ruvnet/agentic-flow> /plugin install agentic-flow@agentic-flow
Cursor
Cursor also loads subagents from .claude/agents, so copy this file there to use it in Cursor.
name: Benchmark Suite type: agent category: optimization description: Comprehensive performance benchmarking, regression detection and performance validation
// Advanced benchmarking system
class ComprehensiveBenchmarkSuite {
constructor() {
this.benchmarks = {
// Core performance benchmarks
throughput: new ThroughputBenchmark(),
latency: new LatencyBenchmark(),
scalability: new ScalabilityBenchmark(),
resource_usage: new ResourceUsageBenchmark(),
// Swarm-specific benchmarks
coordination: new CoordinationBenchmark(),
load_balancing: new LoadBalancingBenchmark(),
topology: new TopologyBenchmark(),
fault_tolerance: new FaultToleranceBenchmark(),
// Custom benchmarks
custom: new CustomBenchmarkManager()
};
this.reporter = new BenchmarkReporter();
this.comparator = new PerformanceComparator();
this.analyzer = new BenchmarkAnalyzer();
}
// Execute comprehensive benchmark suite
async runBenchmarkSuite(config = {}) {
const suiteConfig = {
duration: config.duration || 300000, // 5 minutes default
iterations: config.iterations || 10,
warmupTime: config.warmupTime || 30000, // 30 seconds
cooldownTime: config.cooldownTime || 10000, // 10 seconds
parallel: config.parallel || false,
baseline: config.baseline || null
};
const results = {
summary: {},
detailed: new Map(),
baseline_comparison: null,
recommendations: []
};
// Warmup phase
await this.warmup(suiteConfig.warmupTime);
// Execute benchmarks
if (suiteConfig.parallel) {
results.detailed = await this.runBenchmarksParallel(suiteConfig);
} else {
results.detailed = await this.runBenchmarksSequential(suiteConfig);
}
// Generate summary
results.summary = this.generateSummary(results.detailed);
// Compare with baseline if provided
if (suiteConfig.baseline) {
results.baseline_comparison = await this.compareWithBaseline(
results.detailed,
suiteConfig.baseline
);
}
// Generate recommendations
results.recommendations = await this.generateRecommendations(results);
// Cooldown phase
await this.cooldown(suiteConfig.cooldownTime);
return results;
}
// Parallel benchmark execution
async runBenchmarksParallel(config) {
const benchmarkPromises = Object.entries(this.benchmarks).map(
async ([name, benchmark]) => {
const result = await this.executeBenchmark(benchmark, name, config);
return [name, result];
}
);
const results = await Promise.all(benchmarkPromises);
return new Map(results);
}
// Sequential benchmark execution
async runBenchmarksSequential(config) {
const results = new Map();
for (const [name, benchmark] of Object.entries(this.benchmarks)) {
const result = await this.executeBenchmark(benchmark, name, config);
results.set(name, result);
// Brief pause between benchmarks
await this.sleep(1000);
}
return results;
}
}// Advanced regression detection system
class RegressionDetector {
constructor() {
this.detectors = {
statistical: new StatisticalRegressionDetector(),
machine_learning: new MLRegressionDetector(),
threshold: new ThresholdRegressionDetector(),
trend: new TrendRegressionDetector()
};
this.analyzer = new RegressionAnalyzer();
this.alerting = new RegressionAlerting();
}
// Detect performance regressions
async detectRegressions(currentResults, historicalData, config = {}) {
const regressions = {
detected: [],
severity: 'none',
confidence: 0,
analysis: {}
};
// Run multiple detection algorithms
const detectionPromises = Object.entries(this.detectors).map(
async ([method, detector]) => {
const detection = await detector.detect(currentResults, historicalData, config);
return [method, detection];
}
);
const detectionResults = await Promise.all(detectionPromises);
// Aggregate detection results
for (const [method, detection] of detectionResults) {
if (detection.regression_detected) {
regressions.detected.push({
method,
...detection
});
}
}
// Calculate overall confidence and severity
if (regressions.detected.length > 0) {
regressions.confidence = this.calculateAggregateConfidence(regressions.detected);
regressions.severity = this.calculateSeverity(regressions.detected);
regressions.analysis = await this.analyzer.analyze(regressions.detected);
}
return regressions;
}
// Statistical regression detection using change point analysis
async detectStatisticalRegression(metric, historicalData, sensitivity = 0.95) {
// Use CUSUM (Cumulative Sum) algorithm for change point detection
const cusum = this.calculateCUSUM(metric, historicalData);
// Detect change points
const changePoints = this.detectChangePoints(cusum, sensitivity);
// Analyze significance of changes
const analysis = changePoints.map(point => ({
timestamp: point.timestamp,
magnitude: point.magnitude,
direction: point.direction,
significance: point.significance,
confidence: point.confidence
}));
return {
regression_detected: changePoints.length > 0,
change_points: analysProduction-ready AI agent orchestration with 66 self-learning agents, 213 MCP tools, and autonomous multi-agent swarms.
Advanced code quality analysis agent for comprehensive code reviews and improvements
Advanced code quality analysis agent for comprehensive code reviews and improvements
Expert agent for system architecture design, patterns, and high-level technical decisions
Use this agent when you need to create foundational templates, boilerplate code, or starter configurations for new projects,…
Specialized agents for distributed consensus mechanisms and fault-tolerant coordination protocols
Coordinates Byzantine fault-tolerant consensus protocols with malicious actor detection
Surgical 1-2 file edit. Typo fixes, single-function rewrites, mechanical renames, comment removal, format-preserving tweaks. Hard…