ReddRadar
Agent skill
worker-benchmarks
Run comprehensive worker system benchmarks and performance analysis
Install this agent skill to your Project
npx add-skill https://github.com/ruvnet/ruflo/tree/main/.agents/skills/worker-benchmarks
SKILL.md
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
- Model Cache: Enable with
CLAUDE_FLOW_MODEL_CACHE_MB=512 - Parallel Workers: Enable with
CLAUDE_FLOW_WORKER_PARALLEL=true - Warning Suppression: Enable with
CLAUDE_FLOW_SUPPRESS_WARNINGS=true - SQLite WAL Mode: Automatic for better concurrent performance
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