# Qdrant Hybrid Search Prefetches

> Constructing prefetch queries for hybrid retrieval, including sparse/dense and multi-field setups, and choosing a sparse embedding model. Use when someone asks 'dense and sparse in one search?', 'how to combine multiple fields for retrieval?', 'payloads or sparse vectors for lexical?', 'which sparse embedding model to use?', or 'BM25 vs SPLADE?

## Facts
- Page: https://tashan.sh/capability/skill-qdrant-qdrant-hybrid-search-prefetches
- tashan id: skill:qdrant/qdrant-hybrid-search-prefetches
- Source: https://github.com/qdrant/skills
- Type: skill
- Category: ai
- tashan score: not scored (catalogued only — too little public evidence)
- Adoption: 9.0
- Upkeep: 96.0
- Freshness: 92.0
- Evidence coverage: 84% of the inputs this score can use
- Health: active
- Instruction depth: not yet graded
- License: Apache-2.0
- Official: no

## Install

```sh
cp -r qdrant-hybrid-search-prefetches ~/.claude/skills/
```

## Security audit
Not scanned. We audit npm-published capabilities; this one has no npm package we can resolve, or has not reached the queue. This is not a clean bill of health.

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Measured 2026-08-21 by tashan (https://tashan.sh) from public evidence. Scorer s5.