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Official agent skill

Qdrant Scaling Query Volume

by qdrant in qdrant/skills

Guides Qdrant query volume scaling. An agent skill from qdrant/skills.

OfficialApache-2.0Auto-check passedDatabases

Install Qdrant Scaling Query Volume

skills CLI
$ npx skills add qdrant/skills --skill qdrant-scaling-query-volume -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install qdrant/skills qdrant-scaling-query-volume --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/qdrant/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/qdrant-scaling/scaling-query-volume .claude/skills/qdrant-scaling-query-volume && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
qdrant-scaling-query-volume
GitHub stars
253
Used in
2 other repos
Token cost
~351 tokens
SKILL.md length
165 words
Files
1
Skills in repo
33
Repo updated
First seen
Licence
Apache-2.0

At a glance

Guides Qdrant query volume scaling. An agent skill from qdrant/skills.

  • Someone asks query returns too many results
  • SKILL.md covers Core idea, When it activates and Key tradeoff
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Scroll performance

What it does

Qdrant Scaling Query Volume is an agent skill from qdrant/skills, published by the product's own GitHub organization. Guides Qdrant query volume scaling. Use when someone asks 'query returns too many results', 'scroll performance', 'large limit values', 'paginating search results', 'fetching many vectors', or 'high cardinality results'.

Its SKILL.md is about 350 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases, covering Vector databases. It works with Qdrant. The repository describes itself as: Agent skills for Qdrant vector search: scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage across Python…. The licence is Apache-2.0.

When your agent uses it

  • Someone asks query returns too many results
  • Scroll performance
  • Large limit values
  • Paginating search results

Example prompts

  • “query returns too many results”
  • “scroll performance”
  • “large limit values”
  • “/qdrant-scaling-query-volume”

What it can do on your machine

Read from SKILL.md and the folder at commit 476a18d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Qdrant Scaling Query Volume loads about 351 tokens when it runs. Until then it costs about 62 tokens; SKILL.md has 165 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~62
When it runs · the whole SKILL.md, loaded when a task matches
~351

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from qdrant/skills at commit 476a18d, republished under its Apache-2.0 licence (© qdrant). 165 words, ~351 tokens.

Download SKILL.mdSave it as .claude/skills/qdrant-scaling-query-volume/SKILL.md (or your agent's skills folder).
name
qdrant-scaling-query-volume
description
Guides Qdrant query volume scaling. Use when someone asks 'query returns too many results', 'scroll performance', 'large limit values', 'paginating search results', 'fetching many vectors', or 'high cardinality results'.

Scaling for Query Volume

Problem: When a query has a large limit (e.g. 1000) and there are multiple shards (e.g. 10), naively each shard must return the full 1000 results — totaling 10,000 scored points transferred and merged. This is wasteful since data is randomly distributed across auto-shards.

Core idea

Instead of asking every shard for the full limit, ask each shard for a smaller limit computed via Poisson distribution statistics, then merge. This is safe because auto-sharding guarantees random, independent data distribution.

When it activates

  • More than 1 shard
  • Auto-sharding is in use (all queried shards share the same shard key)
  • The request's limit + offset >= SHARD_QUERY_SUBSAMPLING_LIMIT (128)
  • The query is not exact

Key tradeoff

The strategy trades a small probability of slightly incomplete results for a large reduction in inter-shard data transfer, especially for high-limit queries across many shards. The 1.2x safety factor and the 99.9% Poisson threshold keep the error rate very low — comparable to inaccuracies already introduced by approximate vector indices like HNSW.

© qdrant, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/qdrant-scaling/scaling-query-volume of qdrant/skills.

Open the folder on GitHubat commit 476a18d

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in qdrant/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Qdrant Scaling Query Volume next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Qdrant Scaling Query Volume compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Qdrant Scaling Query Volume this skillqdrant/skills2532 repos~351Automated safety check: PassApache-2.0
Qdrant Performance Optimizationgithub/awesome-copilot40k1 repos~461Automated safety check: PassMIT
Qdrant Scalinggithub/awesome-copilot40k1 repos~467Automated safety check: PassMIT
Codebase Explorationgiancarloerra/SocratiCode3.3k1 repos~1.5kAutomated safety check: PassAGPL-3.0
Qdrant Vector SearchOrchestra-Research/AI-Research-SKILLs13k5 repos~3.4kAutomated safety check: PassMIT
Using Vector Databasesancoleman/ai-design-components5261 repos~3.5kAutomated safety check: PassMIT

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Works with

Categories

Questions about Qdrant Scaling Query Volume

What does Qdrant Scaling Query Volume do?

Guides Qdrant query volume scaling. An agent skill from qdrant/skills. Qdrant Scaling Query Volume is an agent skill from qdrant/skills, published by the product's own GitHub organization. Guides Qdrant query volume scaling.

When should I use Qdrant Scaling Query Volume?

Qdrant Scaling Query Volume fits situations like: someone asks query returns too many results; scroll performance; large limit values; paginating search results.

How do I install Qdrant Scaling Query Volume in Claude Code?

Run `npx skills add qdrant/skills --skill qdrant-scaling-query-volume -a claude-code`. Or copy the skill folder (skills/qdrant-scaling/scaling-query-volume in qdrant/skills) into .claude/skills/qdrant-scaling-query-volume in your project. Claude Code loads it when a task matches its description.

How do I install Qdrant Scaling Query Volume in Codex?

Run `npx skills add qdrant/skills --skill qdrant-scaling-query-volume -a codex`. Or copy the skill folder (skills/qdrant-scaling/scaling-query-volume in qdrant/skills) into .agents/skills/qdrant-scaling-query-volume in your project. Codex loads it when a task matches its description.

Can I use Qdrant Scaling Query Volume in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add qdrant/skills --skill qdrant-scaling-query-volume -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qdrant-scaling-query-volume, .gemini/skills/qdrant-scaling-query-volume, .github/skills/qdrant-scaling-query-volume and .opencode/skills/qdrant-scaling-query-volume in your project.

What does Qdrant Scaling Query Volume need to run?

SKILL.md names no scripts, command-line tools or credentials: Qdrant Scaling Query Volume is instructions for the agent only.

Does Qdrant Scaling Query Volume access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Qdrant Scaling Query Volume safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Qdrant Scaling Query Volume use?

Qdrant Scaling Query Volume is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Qdrant Scaling Query Volume use?

About 351 tokens (SKILL.md is roughly 1.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Qdrant Scaling Query Volume?

Skills that share tags, products or a category with Qdrant Scaling Query Volume: Qdrant Performance Optimization (github/awesome-copilot, 40k stars), Qdrant Scaling (github/awesome-copilot, 40k stars), Codebase Exploration (giancarloerra/SocratiCode, 3.3k stars) and Qdrant Vector Search (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Qdrant Scaling Query Volume?

qdrant (a GitHub organization, an official publisher) maintains it in qdrant/skills, which has 253 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 6, 2026.

Source: qdrant/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.