Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastructure.
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Use vector-index-tuning to propose and benchmark a tuning plan for [vector index] using [workload targets] and [ground-truth queries], reporting recall, latency, and memory; validate on staging before any production rollout.
Required inputs
[vector index]
[workload targets]
[ground-truth queries]
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SKILL.md
name: vector-index-tuningdescription: "Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastructure."risk: safesource: communitydate_added: "2026-02-27"
Vector Index Tuning
Guide to optimizing vector indexes for production performance.
Use this skill when
Tuning HNSW parameters
Implementing quantization
Optimizing memory usage
Reducing search latency
Balancing recall vs speed
Scaling to billions of vectors
Do not use this skill when
You only need exact search on small datasets (use a flat index)
You lack workload metrics or ground truth to validate recall
You need end-to-end retrieval system design beyond index tuning
Instructions
Gather workload targets (latency, recall, QPS), data size, and memory budget.
Choose an index type and establish a baseline with default parameters.
Benchmark parameter sweeps using real queries and track recall, latency, and memory.
Validate changes on a staging dataset before rolling out to production.
Refer to resources/implementation-playbook.md for detailed patterns, checklists, and templates.
Safety
Avoid reindexing in production without a rollback plan.
Validate changes under realistic load before applying globally.
Track recall regressions and revert if quality drops.
Resources
resources/implementation-playbook.md for detailed patterns, checklists, and templates.
Limitations
Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.