
Worker Benchmarks
- 995 installs
- 67k repo stars
- Updated August 4, 2026
- ruvnet/ruflo
worker-benchmarks is an agentic-flow skill at version 1.0.0 that runs comprehensive worker system benchmarks and performance analysis for developers who must optimize background workers before scaling.
About
worker-benchmarks is a version 1.0.0 invocable skill from ruvnet/ruflo for the agentic-flow worker system. It runs npx agentic-flow workers benchmark for a full suite or targets four benchmark types: trigger-detection, registry, agent-selection, and concurrent. Capabilities include performance_testing, metrics_collection, and optimization_recommendations so engineers can profile worker bottlenecks before scaling task dispatch. Developers reach for worker-benchmarks when agentic-flow workers need quantified baselines instead of guessing registry or selection latency under load.
- Runs 5 specialized benchmark suites including trigger-detection, registry, agent-selection, model cache, and concurrent
- Delivers p95 latency targets, throughput, histograms, hit rates, and per-operation breakdowns
- Provides optimization recommendations based on real performance data
- Supports both full benchmark suite and targeted single-type runs via CLI flags
Worker Benchmarks by the numbers
- 995 all-time installs (skills.sh)
- +5 installs in the week ending Aug 4, 2026 (Skillselion tracking)
- Ranked #1,092 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 995 |
|---|---|
| repo stars | ★ 67k |
| Security audit | 3 / 3 scanners passed |
| Last updated | August 4, 2026 |
| Repository | ruvnet/ruflo ↗ |
How do you benchmark agentic-flow worker performance?
Measure and optimize the performance of their agentic worker system before scaling.
Who is it for?
Developers running agentic-flow background workers who need typed benchmarks before scaling concurrent dispatch.
Skip if: Projects not using agentic-flow workers or teams needing only LLM token-cost profiling.
When should I use this skill?
A developer asks to benchmark agentic-flow workers, measure trigger-detection or agent-selection latency, or optimize worker registry performance.
What you get
Worker benchmark metrics, performance analysis output, and optimization recommendations for agentic-flow background workers.
- Worker benchmark metrics report
- Optimization recommendations
By the numbers
- Version 1.0.0 invocable skill with 3 declared capabilities: performance_testing, metrics_collection, optimization_recomm
- Supports 4 benchmark types: trigger-detection, registry, agent-selection, and concurrent
Files
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 concurrentBenchmark 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
Related skills
How it compares
Choose worker-benchmarks for agentic-flow worker CLI benchmarks rather than generic HTTP load generators.
FAQ
What benchmark types does worker-benchmarks support?
worker-benchmarks supports four agentic-flow worker benchmark types—trigger-detection, registry, agent-selection, and concurrent—via npx agentic-flow workers benchmark --type flags or a full suite run without --type.
What CLI command starts worker-benchmarks?
worker-benchmarks starts with npx agentic-flow workers benchmark for the full suite, or npx agentic-flow workers benchmark --type with trigger-detection, registry, agent-selection, or concurrent for targeted runs.
Is Worker Benchmarks safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.