ClaudeSuperPower
SubmitLog in

storing-and-querying-vectors

Skill

Store and query vector embeddings using Amazon S3 Vectors, a cost-effective long-term vector storage service with its own API namespace (s3vectors). Triggers on: create S3 vector bucket, vector index, store embeddings, semantic search, RAG vector storage, similarity search, vector database, migrate

0Machine Learning

Install

git clone https://github.com/aws/agent-toolkit-for-aws.git ~/.claude/skills/storing-and-querying-vectors

What is storing-and-querying-vectors?

Store and query vector embeddings using Amazon S3 Vectors, a cost-effective long-term vector storage service with its own API namespace (s3vectors). Triggers on: create S3 vector bucket, vector index, store embeddings, semantic search, RAG vector storage, similarity search, vector database, migrate from other vector databases. Do NOT use for: querying tabular data (use querying-data-lake), S3 object storage, or hundreds/thousands of sustained QPS (use OpenSearch).

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~117 tokens of context used while enabled, before you invoke anything

Documentation

README · ~4 min read

Store and Query Vectors with Amazon S3 Vectors

Overview

Amazon S3 Vectors is a cost-effective AWS service for storing and querying vector embeddings at scale. Optimized for long-term storage with subsecond latency for cold queries, as low as 100ms for warm queries.

Decision Guide

  • Hundreds/thousands of sustained queries per second (QPS): Wrong tool. Recommend OpenSearch.
  • Hybrid search, aggregations, faceted search: Recommend OpenSearch with S3 Vectors as storage engine. For OpenSearch integration, search AWS docs for "Using S3 Vectors with OpenSearch Service".
  • Tiered (bulk + hot): S3 Vectors for storage + OpenSearch Serverless for real-time. See references/limits-and-patterns.md.
  • Cost-effective storage, infrequent queries, RAG: S3 Vectors is the right fit. Proceed.

For latest guidance, search AWS docs for "S3 Vectors best practices".

Common Tasks

Reviews

Log in to leave a review.

No reviews yet — be the first.

Explore related

Other things in this space — across every part of the ecosystem, not just skills.