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/qdrant-performance-optimization

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

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qdrant
23632 skills
Install
$ npx -y skills add qdrant/skills --skill qdrant-performance-optimization --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/qdrant-performance-optimization

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

qdrant-performance-optimization.SKILL.md
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.

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Agent skills for building with Qdrant vector search Skills encode deep Qdrant knowledge so coding agents can make the engineering decisions that determine whether vector search works well: quantization, sharding, tenant isolation, hybrid search, model

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