From upstash
Skills for Upstash Vector features, TypeScript/JavaScript SDK usage, and integrations. Use when users ask how to work with Vector, its TS SDK, features, or supported frameworks.
npx claudepluginhub upstash/skills --plugin upstashThis skill uses the workspace's default tool permissions.
Vector is a high‑performance vector database for storing, querying, and managing vector embeddings.
Mandates invoking relevant skills via tools before any response in coding sessions. Covers access, priorities, and adaptations for Claude Code, Copilot CLI, Gemini CLI.
Share bugs, ideas, or general feedback.
Vector is a high‑performance vector database for storing, querying, and managing vector embeddings.
Basic workflow:
Example (TypeScript):
import { Index } from "@upstash/vector";
const index = new Index({
url: process.env.UPSTASH_VECTOR_REST_URL!,
token: process.env.UPSTASH_VECTOR_REST_TOKEN!,
});
await index.upsert([{ id: "1", vector: [0.1, 0.2], metadata: { tag: "example" } }]);
const results = await index.query({
vector: [0.1, 0.2],
topK: 5,
});
For full usage, refer to the linked skill files below.
sdk-methods: Explains SDK commands: delete, fetch, info, query, range, reset, resumable-query, upsertfeatures/namespaces: Explains namespaces and dataset organization.features/index-structure: Covers hybrid and sparse index structures.features/filtering-and-metadata: Details metadata storage and server-side filtering.Use these files for deeper guidance on SDK usage, advanced configurations, algorithms, and integrations.