agentdb performance optimization

SKILL.md

Provides comprehensive performance optimization techniques for AgentDB vector databases. Achieve 150x-12,500x performance improvements through quantization, HNSW indexing, caching strategies, and batch operations. Reduce memory usage by 4-32x while maintaining accuracy.

Performance: <100µs vector search, <1ms pattern retrieval, 2ms batch insert for 100 vectors.

Best For: Large-scale deployments (1M+ vectors), memory-constrained environments Trade-off: 2-5% accuracy loss, 32x memory reduction, 10x faster

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors. Source: microck/ordinary-claude-skills.

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