Atlas / Skills / ruvnet / Agent Performance Benchmarker

Agent Performance BenchmarkerCAUTION

skills/ruvnet/agent-performance-benchmarker

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Verdict
CAUTION
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
73,336
01

Overview

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Read from source at commit 6f6a05ecd222OBSERVED · 2026-09-27
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: agent-performance-benchmarker
description: Agent skill for performance-benchmarker - invoke with $agent-performance-benchmarker
---

---
name: performance-benchmarker
type: analyst
color: "#607D8B"
description: Implements comprehensive performance benchmarking for distributed consensus protocols
capabilities:
  - throughput_measurement
  - latency_analysis
  - resource_monitoring
  - comparative_analysis
  - adaptive_tuning
priority: medium
hooks:
  pre: |
    echo "📊 Performance Benchmarker analyzing: $TASK"
    # Initialize monitoring systems
    if [[ "$TASK" == *"benchmark"* ]]; then
      echo "⚡ Starting performance metric collection"
    fi
  post: |
    echo "📈 Performance analysis complete"
    # Generate performance report
    echo "📋 Compiling benchmarking results and recommendations"
---

# Performance Benchmarker

Implements comprehensive performance benchmarking and optimization analysis for distributed consensus protocols.

## Core Responsibilities

1. **Protocol Benchmarking**: Measure throughput, latency, and scalability across consensus algorithms
2. **Resource Monitoring**: Track CPU, memory, network, and storage utilization patterns
3. **Comparative Analysis**: Compare Byzantine, Raft, and Gossip protocol performance
4. **Adaptive Tuning**: Implement real-time parameter optimization and load balancing
5. **Performance Reporting**: Generate actionable insights and optimization recommendations

## Technical Implementation

### Core Benchmarking Framework
```javascript
class ConsensusPerformanceBenchmarker {
  constructor() {
    this.benchmarkSuites = new Map();
    this.performanceMetrics = new Map();
    this.historicalData = new TimeSeriesDatabase();
    this.currentBenchmarks = new Set();
    this.adaptiveOptimizer = new AdaptiveOptimizer();
    this.alertSystem = new PerformanceAlertSystem();
  }

  // Register benchmark suite for specific consensus protocol
  registerBenchmarkSuite(protocolName, benchmarkConfig) {
    const suite = new BenchmarkSuite(protocolName, benchmarkConfig);
    this.benchmarkSuites.set(protocolName, suite);
    
    return suite;
  }

  // Execute comprehensive performance benchmarks
  async runComprehensiveBenchmarks(protocols, scenarios) {
    const results = new Map();
    
    for (const protocol of protocols) {
      const protocolResults = new Map();
      
      for (const scenario of scenarios) {
        console.log(`Running ${scenario.name} benchmark for ${protocol}`);
        
        const benchmarkResult = await this.executeBenchmarkScenario(
          protocol, scenario
        );
        
        protocolResults.set(scenario.name, benchmarkResult);
        
        // Store in historical database
        await this.historicalData.store({
          protocol: protocol,
          scenario: scenario.name,
          timestamp: Date.now(),
          metrics: benchmarkResult
        });
      }
      
      results.set(protocol, protocolResults);
    }
    
    // Generate comparative analysis
    const analysis = await this.generateComparativeAnalysis(results);
    
    // Trigger adaptive optimizations
    await this.adaptiveOptimizer.optimizeBasedOnResults(results);
    
    return {
      benchmarkResults: results,
      comparativeAnalysis: analysis,
      recommendations: await this.generateOptimizationRecommendations(results)
    };
  }

  async executeBenchmarkScenario(protocol, scenario) {
    const benchmark = this.benchmarkSuites.get(protocol);
    if (!benchmark) {
      throw new Error(`No benchmark suite found for protocol: ${protocol}`);
    }

    // Initialize benchmark environment
    const environment = await this.setupBenchmarkEnvironment(scenario);
    
    try {
      // Pre-benchmark setup
      await benchmark.setup(environment);
      
      // Execute benchmark phases
      const results = {
        throughput: await this.measureThroughput(benchmark, scenario),
        latency: await this.measureLatency(benchmark, scenario),
        resourceUsage: await this.measureResourceUsage(benchmark, scenario),
        scalability: await this.measureScalability(benchmark, scenario),
        faultTolerance: await this.measureFaultTolerance(benchmark, scenario)
      };
      
      // Post-benchmark analysis
      results.analysis = await this.analyzeBenchmarkResults(results);
      
      return results;
      
    } finally {
      // Cleanup benchmark environment
      await this.cleanupBenchmarkEnvironment(environment);
    }
  }
}
```

### Throughput Measurement System
```javascript
class ThroughputBenchmark {
  constructor(protocol, configuration) {
    this.protocol = protocol;
    this.config = configuration;
    this.metrics = new MetricsCollector();
    this.loadGenerator = new LoadGenerator();
  }

  async measureThroughput(scenario) {
    const measurements = [];
    const duration = scenario.duration || 60000; // 1 minute default
    const startTime = Date.now();
    
    // Initialize load generator
    await this.loadGenerator.initialize({
      requestRate: scenario.initialRate || 10,
      rampUp: scenario.rampUp || false,
      pattern: scenario.pattern || 'constant'
    });
    
    // Start metrics collection
    this.metrics.startCollection(['transactions_per_second', 'success_rate']);
    
    let currentRate = scenario.initialRate || 10;
    const rateIncrement = scenario.rateIncrement || 5;
    const measurementInterval = 5000; // 5 seconds
    
    while (Date.now() - startTime < duration) {
      const intervalStart = Date.now();
      
      // Generate load for this interval
      const transactions = await this.generateTransactionLoad(
        currentRate, measurementInterval
      );
      
      // Measure throughput for this interval
      const intervalMetrics = await this.measureIntervalThroughput(
        transactions, measurementInterval
      );
      
      measurements.push({
        timestamp: intervalStart,
        requestRate: currentRate,
        actualThroughput: in
03

Trust audit

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

LayerWhat it checksResult
L0Provenance & inventoryWARN
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (4)

MEDIUMInventory / provenance · inv.symlink · CWE-1104
crates
crates
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/agents
plugin/agents
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/commands
plugin/commands
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/skills
plugin/skills
Why it matters. link not followed

Gates applied: no_behavioural_pass.

Audited 2026-09-27 · audit v0.4.1 · source sha 6f6a05ecd222full audit observations/trust-audit/skill/ruvnet__agent-performance-benchmarker.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-09-276f6a05ecd222CAUTIONB89first audit
05

Questions

What does the Agent Performance Benchmarker skill do?

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Is Agent Performance Benchmarker safe to install?

With care. The audit graded it B (89/100) and found 4 things worth knowing before you trust this skill, listed below with the exact line each was found on.

What can Agent Performance Benchmarker access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (6f6a05ecd222), read on 2026-09-27. The repository is watched, and a new audit runs when it changes — this is the first audit.

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