worker-benchmarks
Run comprehensive worker system benchmarks and performance analysis
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- ruvnet/ruflo
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- 25 mars 2026 à 20:28
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SKILL.md
Instructions source · Aperçu en lecture seule- name
- worker-benchmarks
- description
- Run comprehensive worker system benchmarks and performance analysis
- user-invocable
- true
# Worker Benchmarks Skill
Run comprehensive performance benchmarks for the agentic-flow worker system.
## Quick Start
```bash
# 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`:
```json
{
"performance": {
"benchmarkThresholds": {
"triggerDetection": { "p95Ms": 5 },
"workerRegistry": { "p95Ms": 10 },
"agentSelection": { "p95Ms": 1 },
"memoryKeyGeneration": { "p95Ms": 0.1 },
"concurrentWorkers": { "totalMs": 1000 }
}
}
}
```
## Programmatic Usage
```typescript
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
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