AI/ML

vector-index-tuning

sickn33/antigravity-awesome-skills · updated Apr 8, 2026

$npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill vector-index-tuning
summary

Guide to optimizing vector indexes for production performance.

skill.md

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

  1. Gather workload targets (latency, recall, QPS), data size, and memory budget.
  2. Choose an index type and establish a baseline with default parameters.
  3. Benchmark parameter sweeps using real queries and track recall, latency, and memory.
  4. 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.
general reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    vector-index-tuning is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Piyush G· Sep 9, 2024

    Keeps context tight: vector-index-tuning is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Aug 8, 2024

    Registry listing for vector-index-tuning matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Sakshi Patil· Jul 7, 2024

    vector-index-tuning reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ganesh Mohane· Jun 6, 2024

    I recommend vector-index-tuning for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Oshnikdeep· May 5, 2024

    Useful defaults in vector-index-tuning — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Dhruvi Jain· Apr 4, 2024

    vector-index-tuning has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Rahul Santra· Mar 3, 2024

    Solid pick for teams standardizing on skills: vector-index-tuning is focused, and the summary matches what you get after install.

  • Pratham Ware· Feb 2, 2024

    We added vector-index-tuning from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Yash Thakker· Jan 1, 2024

    vector-index-tuning fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.