Skip to main content
skill CX Codex

qdrant-performance-optimization · qdrant — Claude Code skill for Qdrant tuning

A routing skill for Qdrant tuning: it matches your symptom to the right sub-skill for search speed, indexing or memory.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add qdrant/skills --skill qdrant-performance-optimization -a claude-code
Open on GitHub

What qdrant-performance-optimization does

The skill holds no advice of its own. You describe a symptom, it matches that against a table and opens the matching sub-skill file — search-speed-optimization/SKILL.md, indexing-performance-optimization/SKILL.md or memory-usage-optimization/SKILL.md. Answers come from there, not from the hub page.

Use it when you are planning a configuration or capacity change rather than firefighting. Slow filtered queries, low QPS, a collection stuck yellow, an optimizer that will not finish, bulk upserts dragging, RAM pressure — each maps to a different branch, and if two rows match, both files get read.

One thing to get right: latency and throughput pull in opposite directions on segment count. For latency you raise segments toward the CPU core count (default_segment_number: 16); for throughput you go fewer and larger (default_segment_number: 2). Picking the wrong direction makes the reported problem worse. If the slowdown is already happening in production or you need live metrics, that is qdrant-monitoring territory. The skill is limited to Read, Grep and Glob.

What it helps with

  • route a Qdrant symptom to the right sub-skill
  • pick segment count for latency or for throughput
  • speed up index and HNSW builds and vector uploads
  • cut RAM use and avoid out-of-memory crashes
  • fit a larger dataset on the same hardware

Example prompts for the agent

  • Filtered queries in Qdrant are much slower than unfiltered ones — where do I look?
  • My collection stays yellow and the optimizer never finishes, help me sort it out
  • I want to lower Qdrant RAM usage without shrinking the dataset

How to install qdrant-performance-optimization

1Skills CLI (Vercel)

npx skills add qdrant/skills --skill qdrant-performance-optimization -a claude-code

2Manually: put the files in place

~/.claude/skills/qdrant-performance-optimization/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/qdrant-performance-optimization/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about qdrant-performance-optimization

How do I install qdrant-performance-optimization in Claude?

Run npx skills add qdrant/skills --skill qdrant-performance-optimization -a claude-code. The skill file lands at ~/.claude/skills/qdrant-performance-optimization/SKILL.md.

What does qdrant-performance-optimization do?

It matches your symptom against a table and opens the relevant sub-skill: search speed, indexing performance or memory usage. The hub page itself carries routing only, no guidance.

How is it different from qdrant-monitoring?

This one is for planned configuration and capacity changes. For an active production slowdown or live metrics analysis, use qdrant-monitoring.

Source text

SKILL.md · Apache-2.0
---
name: qdrant-performance-optimization
description: "Navigation hub linking sub-skills for proactive Qdrant tuning: search speed, indexing performance, and memory usage optimization. Use when planning configuration or capacity changes to improve speed and efficiency. For diagnosing an active production slowdown or analyzing live metrics, use qdrant-monitoring instead."
allowed-tools:
  - Read
  - Grep
  - Glob
---


# Qdrant Performance Optimization

Route first, then answer. Match the user's symptom in the table, `Read` that file, and answer from it.
Do not answer from this page alone: it contains routing only, not the guidance. If two rows match, read both.

| The user says | Read |
|---|---|
| Filtered queries much slower than unfiltered | `search-speed-optimization/SKILL.md` |
| Low QPS, cannot handle the query load | `search-speed-optimization/SKILL.md` |
| Individual queries take too long to return | `search-speed-optimization/SKILL.md` |
| Index build or HNSW build takes too long, vector upload is slow | `indexing-performance-optimization/SKILL.md` |
| Collection stays yellow, optimizer stuck or runs for a long time | `indexing-performance-optimization/SKILL.md` |
| Bulk upsert of vectors is slow | `indexing-performance-optimization/SKILL.md` |
| RAM usage too high, out-of-memory crashes | `memory-usage-optimization/SKILL.md` |
| Want to fit a larger dataset on the same hardware | `memory-usage-optimization/SKILL.md` |
| Reducing cost by moving data to disk | `memory-usage-optimization/SKILL.md` |

Latency and throughput pull opposite ways on segment count.
For latency, increase segments toward the CPU core count (`default_segment_number: 16`).
For throughput, use fewer and larger segments (`default_segment_number: 2`).
Applying the wrong direction makes the reported problem worse.

© qdrant · Apache-2.0 · qdrant/skills

Similar skills

All skills for Data and databases →

qdrant-performance-optimization by other authors comes first.

From the same set6

Project sponsors

Companies that keep this analytics open
Gold sponsor

Impressions, clicks and code copies — open statistics. We keep the numbers public for the same reason NeBlask itself is public. Become a sponsor