# Scylladb Vector Search

> | Guides ScyllaDB Cloud users through implementing and optimizing Vector Search for semantic similarity, RAG, and similar use cases. Use this skill when users need to store and query embeddings, build vector indexes (HNSW), run approximate nearest neighbour (ANN) queries, apply filtering (global/local secondary indexes), configure quantization, or integrate with LLM frameworks (e.g. LangChain). Also use when users mention "vector", "embeddings", "similarity search", "ANN", "nearest neighbor", "RAG", "semantic search", or "recommendation system" in the context of ScyllaDB.

## Facts
- Page: https://tashan.sh/capability/skill-scylladb-scylladb-vector-search
- tashan id: skill:scylladb/scylladb-vector-search
- Source: https://github.com/scylladb/agent-skills
- Type: skill
- Category: ai
- tashan score: not scored (catalogued only — too little public evidence)
- Adoption: 9.0
- Upkeep: 98.0
- Freshness: 95.0
- 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 scylladb-vector-search ~/.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 2026-08-05 by tashan (https://tashan.sh) from public evidence. Scorer s5.