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Official agent skill

Qdrant Hybrid Search

by qdrant in qdrant/skills

Explains hybrid search in Qdrant. An agent skill from qdrant/skills.

OfficialApache-2.0Auto-check passedAI & LLM Engineering

Install Qdrant Hybrid Search

skills CLI
$ npx skills add qdrant/skills --skill qdrant-hybrid-search -a claude-code

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

GitHub CLI
$ gh skill install qdrant/skills qdrant-hybrid-search --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-search-quality/search-strategies/hybrid-search .claude/skills/qdrant-hybrid-search && 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-hybrid-search
GitHub stars
254
Token cost
~917 tokens
SKILL.md length
403 words
Files
1
Skills in repo
33
Repo updated
First seen
Licence
Apache-2.0

At a glance

Explains hybrid search in Qdrant. An agent skill from qdrant/skills.

  • Works in 3 steps: Configure Qdrant collection with named… → Construct a hybrid search request with… → Evaluate hybrid search quality on real…
  • Someone asks how do I setup hybrid search?
  • SKILL.md covers How Isolated Are Parallel… and What NOT to Do
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Qdrant Hybrid Search is an agent skill from qdrant/skills, published by the product's own GitHub organization. Explains hybrid search in Qdrant. Use when someone asks 'how do I setup hybrid search?', 'how to combine keyword and semantic search?', 'sparse plus dense vectors?', 'missing keyword matches', 'how to combine results from multiple searches?' and 'combining multiple representations'. Also use for how a hybrid query is scoped: 'how is IDF scoped?', 'can one tenant's data contaminate another tenant's scoring?'

Its SKILL.md is about 920 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 AI & LLM Engineering, covering Retrieval-augmented generation and 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 how do I setup hybrid search?
  • How to combine keyword and semantic search?
  • Sparse plus dense vectors?
  • Missing keyword matches

Example prompts

  • “how do I setup hybrid search?”
  • “how to combine keyword and semantic search?”
  • “sparse plus dense vectors?”
  • “/qdrant-hybrid-search”

Requirements

  • Pre-approved tools (allowed-tools): Read, Grep, Glob

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Configure Qdrant collection with named vectors, where each named vector usually corresponds to one representation (different embedding…
  2. Construct a hybrid search request with Query API from your building blocks. You can search independently among one type of vectors, with…
  3. Evaluate hybrid search quality on real user data and provide user with improvements and tradeoffs (speed/resources).

What it can do on your machine

Read from SKILL.md and the folder at commit 1780b6d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob

    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

    Links to these hosts (documentation or services it may open):

    • skills.qdrant.tech

    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 Hybrid Search loads about 917 tokens when it runs. Until then it costs about 108 tokens; SKILL.md has 403 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~108
When it runs · the whole SKILL.md, loaded when a task matches
~917

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 1780b6d, republished under its Apache-2.0 licence (© qdrant). 403 words, ~917 tokens.

Download SKILL.mdSave it as .claude/skills/qdrant-hybrid-search/SKILL.md (or your agent's skills folder).
name
qdrant-hybrid-search
description
Explains hybrid search in Qdrant. Use when someone asks 'how do I setup hybrid search?', 'how to combine keyword and semantic search?', 'sparse plus dense vectors?', 'missing keyword matches', 'how to combine results from multiple searches?' and 'combining multiple representations'. Also use for how a hybrid query is scoped: 'how is IDF scoped?', 'can one tenant's data contaminate another tenant's scoring?'
allowed-tools
Read, Grep, Glob

Hybrid Search in Qdrant

Hybrid search means running two or more different searches in parallel and combining their results into one.

In Qdrant this is powered by the Query API via prefetch: each prefetch runs exactly one type of search independently, and the outer query combines results from parallel prefetches.
Prefetches can be nested and searches can be multi-stage, all pipeline happening in one request through Query API. See Universal Query API for examples.

Identify the user's problem and pick building blocks:

  • What can go into one prefetch, e.g. power one search, in Search Types
  • How to combine results of these searches and tune the fusion (RRF, DBSF, FormulaQuery, reranking) in Combining Searches

Based on what you've picked, test your approach:

  1. Configure Qdrant collection with named vectors, where each named vector usually corresponds to one representation (different embedding models or different vector types) of a data point.
  2. Construct a hybrid search request with Query API from your building blocks. You can search independently among one type of vectors, with prefetch + using, like shown in examples in Hybrid Queries documentation.
  3. Evaluate hybrid search quality on real user data and provide user with improvements and tradeoffs (speed/resources).
Show full SKILL.md (205 more words)Show less

How Isolated Are Parallel Searches?

Use when: different tenants share one collection and you need to understand hybrid search isolation guarantees.

If user wants to isolate/share hybrid search pipelines between tenants, consider that:

  • Indexes (sparse, payload and dense) and IDF modifier for sparse vectors are computed independently per shard, not per tenant, by default — payload-based tenant partitioning alone does not isolate IDF statistics. On Qdrant 1.19 or newer, the idf search param can scope IDF statistics to a payload-filtered corpus (requires a payload index on the filtered field), giving each tenant properly isolated BM25 scoring instead of shard-wide statistics.
  • Prefetch runs independently per shard to retrieve #limit results, so for collection-level prefetches if collection has several shards, Qdrant will always prefetch under the hood #limit * #shard results. Final results are merged based on scores.
  • In nested prefetches (deeper than 1 level), methods described in "Combining Searches" might be done on a shard level first, then per-shards results once again will be merged based on scores.

What NOT to Do

  • Choose a hybrid search pattern based on "vibes" without any hybrid search quality evaluation in-place.
  • Create too many named vectors without a need. An unfilled named vector might take as much resources as a filled one.

© 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-search-quality/search-strategies/hybrid-search of qdrant/skills.

Open the folder on GitHubat commit 1780b6d

Compare with similar skills

Qdrant Hybrid Search 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 Hybrid Search compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Qdrant Hybrid Search this skillqdrant/skills254—~917Automated safety check: PassApache-2.0
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Hunt RAG Vectorelementalsouls/Claude-BugHunter4.8k—~2.6kAutomated safety check: PassMIT
Qdrant Search Qualitygithub/awesome-copilot40k1 repos~336Automated safety check: PassMIT
QdrantLuciole-Studio/Misaka-Agent1711 repos~3.4kAutomated safety check: PassMIT
Building RAG Systemsaiskillstore/marketplace433—~2.7kAutomated safety check: PassNone

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Works with

Categories

Questions about Qdrant Hybrid Search

What does Qdrant Hybrid Search do?

Explains hybrid search in Qdrant. An agent skill from qdrant/skills. Qdrant Hybrid Search is an agent skill from qdrant/skills, published by the product's own GitHub organization. Explains hybrid search in Qdrant.

When should I use Qdrant Hybrid Search?

Qdrant Hybrid Search fits situations like: someone asks how do I setup hybrid search?; how to combine keyword and semantic search?; sparse plus dense vectors?; missing keyword matches.

How do I install Qdrant Hybrid Search in Claude Code?

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

How do I install Qdrant Hybrid Search in Codex?

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

Can I use Qdrant Hybrid Search 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-hybrid-search -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-hybrid-search, .gemini/skills/qdrant-hybrid-search, .github/skills/qdrant-hybrid-search and .opencode/skills/qdrant-hybrid-search in your project.

What does Qdrant Hybrid Search need to run?

SKILL.md names no scripts, command-line tools or credentials: Qdrant Hybrid Search is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Glob.

Does Qdrant Hybrid Search access the network?

SKILL.md names 1 domain. As links in the text: skills.qdrant.tech. This is read from the text; nothing was executed.

Is Qdrant Hybrid Search 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 Hybrid Search use?

Qdrant Hybrid Search 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 Hybrid Search use?

About 917 tokens (SKILL.md is roughly 3.7k 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 Hybrid Search?

Skills that share tags, products or a category with Qdrant Hybrid Search: RAG Implementation (wshobson/agents, 40k stars), Hunt RAG Vector (elementalsouls/Claude-BugHunter, 4.8k stars), Qdrant Search Quality (github/awesome-copilot, 40k stars) and Qdrant (Luciole-Studio/Misaka-Agent, 171 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Qdrant Hybrid Search?

qdrant (a GitHub organization, an official publisher) maintains it in qdrant/skills, which has 254 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 9, 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.