worker-benchmarks

name	worker-benchmarks
description	Run comprehensive worker system benchmarks and performance analysis
version	1.0.0
invocable	true
author	agentic-flow
capabilities	["performance_testing","metrics_collection","optimization_recommendations"]

Worker Benchmarks Skill

Run comprehensive performance benchmarks for the agentic-flow worker system.

Quick Start

# Run full benchmark suite
npx agentic-flow workers benchmark

# Run specific benchmark
npx agentic-flow workers benchmark --type trigger-detection
npx agentic-flow workers benchmark --type registry
npx agentic-flow workers benchmark --type agent-selection
npx agentic-flow workers benchmark --type concurrent

Benchmark Types

1. Trigger Detection (trigger-detection)

Tests keyword detection speed across 12 worker triggers.

• Target: p95 < 5ms
• Iterations: 1000
• Metrics: latency, throughput, histogram

2. Worker Registry (registry)

Tests CRUD operations on worker entries.

• Target: p95 < 10ms
• Iterations: 500 creates, gets, updates
• Metrics: per-operation latency breakdown

3. Agent Selection (agent-selection)

Tests performance-based agent selection.

• Target: p95 < 1ms
• Iterations: 1000
• Metrics: selection confidence, agent scores

4. Model Cache (cache)

Tests model caching performance.

• Target: p95 < 0.5ms
• Metrics: hit rate, cache size, eviction stats

5. Concurrent Workers (concurrent)

Tests parallel worker creation and updates.

• Target: < 1000ms for 10 workers
• Metrics: per-worker latency, memory usage

6. Memory Key Generation (memory-keys)

Tests memory pattern key generation.

• Target: p95 < 0.1ms
• Iterations: 5000
• Metrics: unique patterns, throughput

Output Format

═══════════════════════════════════════════════════════════
📈 BENCHMARK RESULTS
═══════════════════════════════════════════════════════════

✅ Trigger Detection
   Operation: detect
   Count: 1,000
   Avg: 0.045ms | p95: 0.120ms (target: 5ms)
   Throughput: 22,222 ops/s
   Memory Δ: 0.12MB

✅ Worker Registry
   Operation: crud
   Count: 1,500
   Avg: 1.234ms | p95: 3.456ms (target: 10ms)
   Throughput: 810 ops/s
   Memory Δ: 2.34MB

───────────────────────────────────────────────────────────
📊 SUMMARY
───────────────────────────────────────────────────────────
Total Tests: 6
Passed: 6 | Failed: 0
Avg Latency: 0.567ms
Total Duration: 2345ms
Peak Memory: 8.90MB
═══════════════════════════════════════════════════════════

Integration with Settings

Benchmark thresholds are configured in .claude/settings.json:

{
  "performance": {
    "benchmarkThresholds": {
      "triggerDetection": { "p95Ms": 5 },
      "workerRegistry": { "p95Ms": 10 },
      "agentSelection": { "p95Ms": 1 },
      "memoryKeyGeneration": { "p95Ms": 0.1 },
      "concurrentWorkers": { "totalMs": 1000 }
    }
  }
}

Programmatic Usage

import { workerBenchmarks, runBenchmarks } from 'agentic-flow/workers/worker-benchmarks';

// Run full suite
const suite = await runBenchmarks();
console.log(suite.summary);

// Run individual benchmarks
const triggerResult = await workerBenchmarks.benchmarkTriggerDetection(1000);
const registryResult = await workerBenchmarks.benchmarkRegistryOperations(500);

Performance Optimization Tips

1. Model Cache: Enable with CLAUDE_FLOW_MODEL_CACHE_MB=512
2. Parallel Workers: Enable with CLAUDE_FLOW_WORKER_PARALLEL=true
3. Warning Suppression: Enable with CLAUDE_FLOW_SUPPRESS_WARNINGS=true
4. SQLite WAL Mode: Automatic for better concurrent performance