Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastructure.
8.1
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Data & Analytics
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Excellent skill for vector index optimization with comprehensive parameter tuning guidance, quantization strategies, and production-ready code templates. The description clearly covers when to use the skill (HNSW tuning, quantization, scaling), and the content delivers substantial task knowledge including benchmarking functions, memory estimation, and platform-specific configurations (Qdrant). Structure is clean with well-organized templates and clear parameter tables. Novelty is solid - while vector search is a known domain, the detailed parameter recommendations, quantization comparisons, and performance monitoring code would require significant token expenditure for a CLI agent to replicate. Minor room for improvement: could include more advanced topics like hybrid search or specific cloud platform optimizations, and performance monitoring could be more extensive. Overall, this is a highly practical skill that meaningfully reduces complexity for vector search optimization tasks.
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