Guides Qdrant scaling decisions. Use when someone asks 'how many nodes do I need', 'data doesn't fit on one node', 'need more throughput', 'cluster is slow', 'too many tenants', 'vertical or horizontal', 'how to shard', or 'need to add capacity'.
npx skills add https://github.com/qdrant/skills --skill qdrant-scaling
First determine what you're scaling for:
After determining the scaling goal, we can choose scaling strategy based on tradeoffs and assumptions.
Each pulls toward different strategies. Scaling for throughput and latency are opposite tuning directions.
This becomes relevant when volume of the dataset exceeds the capacity of a single node.
Read more about scaling for data volume in Scaling Data Volume
If your system needs to handle more parallel queries than a single node can handle,
then you need to scale for query throughput.
Read more about scaling for query throughput in Scaling for Query Throughput
Latency of a single query is determined by the slowest component in the query execution path.
It is in sometimes correlated with throughput, but not always. It might require different strategies for scaling.
Read more about scaling for query latency in Scaling for Query Latency
By query volume we understand the amount of results that a single query returns.
If the query volume is too high, it can cause performance issues and increase latency.
Tuning for query volume is opposite might require special strategies.
Read more about scaling for query volume in Scaling for Query Volume
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
Generates creative domain name ideas for your project and checks availability across multiple TLDs (.com, .io, .dev, .ai, etc.). Saves hours of brainstorming and manual checking.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Take qdrant/qdrant-scaling from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.