worker-benchmarks

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Run comprehensive worker system benchmarks and performance analysis

AI & Automation 55,035 stars 6256 forks Updated today MIT

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# 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**: un...

Details

Author
ruvnet
Repository
ruvnet/ruflo
Created
11 months ago
Last Updated
today
Language
TypeScript
License
MIT

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