Agent skill · data analytics · aiskillstore
agentdb-vector-search-optimization
Optimize AgentDB vector search performance using quantization for 4-32x memory reduction, HNSW indexing for 150x faster search, caching, and batch operations for scaling to millions of vectors.
Why this skill is useful
Provides specific techniques and code examples for optimizing vector search performance in AgentDB, which are not widely known.
What it needs
Requires agentdb-optimization installed locally. About 2k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
AgentDB Vector Search Optimization Overview Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations for scaling to millions of vectors. SOP Framework: 5-Phase Optimization Phase 1: Baseline Performance (1 hour) Measure current metrics (latency, throughput, memory) Identify bottlenecks Set optimization targets Phase 2: Apply Quantization (1-2 hours) Configure product quantization Train codebooks Apply compression Validate accuracy Phase 3: Implement HNSW Indexing (1-2 hours) Build HNSW index Tune parameters (M, efConstruction, efSearch) Benchmark speedup Phase 4: Configure Caching (1 hour) Implement query cache Set TTL and eviction policies Monitor hit rates Phase 5: Benchmark Results (1-2 hours) Run comprehensive benchmarks Compare before/after Validate improvements Quick Start Optimization Techniques Quantization Product Quantization: 4-8x compression Scalar Quantization: 2-4x compression Binary Quantization: 32x compression Indexing HNSW: 150x faster, high accuracy IVF: Fast, partitioned search LSH: Approximate search Caching Query Cache: LRU eviction Result Cache: TTL-based Embedding Cache: Reuse embeddings Success Metrics Memory reduction: 4-32x Search speedup: 150x Accuracy maintained: > 95% Cache hit rate: > 70% Additional Resources Full docs: SKILL.md AgentDB Optimization: https://agentdb.dev/docs/optimization
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/agentdb-vector-search-optimization