/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
$ npx -y skills add qdrant/skills --skill qdrant-performance-optimization --agent claude-codeHow 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.mdname: 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:
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Qdrant Performance Optimization
There are different aspects of Qdrant performance, this document serves as a navigation hub for different aspects of performance optimization in Qdrant.
Search Speed Optimization
There are two different criteria for search speed: latency and throughput. Latency is the time it takes to get a response for a single query, while throughput is the number of queries that can be processed in a given time frame. Depending on your use case, you may want to optimize for one or both of these metrics.
More on search speed optimization can be found in the [Search Speed Optimization](search-speed-optimization/SKILL.md) skill.
Indexing Performance Optimization
Qdrant needs to build a vector index to perform efficient similarity search. The time it takes to build the index can vary depending on the size of your dataset, hardware, and configuration.
More on indexing performance optimization can be found in the [Indexing Performance Optimization](indexing-performance-optimization/SKILL.md) skill.
Memory Usage Optimization
Vector search can be memory intensive, especially when dealing with large datasets. Qdrant has a flexible memory management system, which allows you to precisely control which parts of storage are kept in memory and which are stored on disk. This can help you optimize memory usage without sacrificing performance.
More on memory usage optimization can be found in the [Memory Usage Optimization](memory-usage-optimization/SKILL.md) skill.
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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
There are different aspects of Qdrant performance, this document serves as a navigation hub for different aspects of performance optimization in Qdrant.
Search Speed Optimization
There are two different criteria for search speed: latency and throughput. Latency is the time it takes to get a response for a single query, while throughput is the number of queries that can be processed in a given time frame. Depending on your use case, you may want to optimize for one or both of these metrics.
More on search speed optimization can be found in the [Search Speed Optimization](search-speed-optimization/SKILL.md) skill.
Indexing Performance Optimization
Qdrant needs to build a vector index to perform efficient similarity search. The time it takes to build the index can vary depending on the size of your dataset, hardware, and configuration.
More on indexing performance optimization can be found in the [Indexing Performance Optimization](indexing-performance-optimization/SKILL.md) skill.
Memory Usage Optimization
Vector search can be memory intensive, especially when dealing with large datasets. Qdrant has a flexible memory management system, which allows you to precisely control which parts of storage are kept in memory and which are stored on disk. This can help you optimize memory usage without sacrificing performance.
More on memory usage optimization can be found in the [Memory Usage Optimization](memory-usage-optimization/SKILL.md) skill.
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
Repo: qdrant/skills
Other skills on qdrant.
- /qdrant-clients-sdk
Qdrant provides client SDKs for various programming languages, allowing easy integration with Qdrant deployments.
Open skill - /qdrant-deployment-options
Guides Qdrant deployment selection. Use when someone asks 'how to deploy Qdrant', 'Docker vs Cloud', 'local mode', 'embedded Qdrant', 'Qdrant EDGE', 'which deployment option', 'self-hosted vs cloud', or 'need lowest latency deployment'. Also use when choosing between deployment
Open skill - /qdrant-edge
Guides building on Qdrant Edge, the embedded in-process shard. Use when someone asks 'how to sync Edge with the server', 'keep a local shard in sync with Qdrant Cloud', 'BM25 or keyword search on Edge', 'hybrid search on Edge', 'embeddings on device', 'Edge snapshots', 'apply a
Open skill - /qdrant-model-migration
Guides embedding model migration in Qdrant without downtime. Use when someone asks 'how to switch embedding models', 'how to migrate vectors', 'how to update to a new model', 'zero-downtime model change', 'how to re-embed my data', or 'can I use two models at once'. Also use
Open skill - /qdrant-monitoring
Guides Qdrant monitoring and observability setup. Use when someone asks 'how to monitor Qdrant', 'what metrics to track', 'is Qdrant healthy', 'optimizer stuck', 'why is memory growing', 'requests are slow', or needs to set up Prometheus, Grafana, or health checks. Also use when
Open skill - /debugging
Diagnoses Qdrant production issues using metrics and observability tools. Use when someone reports 'optimizer stuck', 'indexing too slow', 'memory too high', 'OOM crash', 'queries are slow', 'latency spike', or 'search was fast now it's slow'. Also use when performance degrades
Open skill