Every premium and members-only resource for $9.99/month, as a no-commitment subscription. See the plans

PalateKit

Sign in
Menu

Request a resource

Describe the resource you are missing in one sentence. We will email you when it is published.

0 / 280

A page, a video or an image online.

Unlock PalateKit

Unlock everything

Plan

Paying means accepting our terms of sale.

Secure payment by Stripe. Receipts and invoices sent by email.

Welcome back

Sign in to install, download or save this resource. A free account is enough for free resources.

Index and search embeddings v1.0.0

Use this resource to generate embeddings and run semantic search in a vector database

New

  • 339 downloads
  • 162 likes
  • 134 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install vector-database-embeddings-search

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent generates embeddings for your texts, stores them in a vector database and runs similarity searches. It covers Pinecone, Weaviate, Chroma and pgvector, along with RAG use cases. You get an index you can query by meaning.

Mostly picked by

Updated November 2, 2026

Card for the “Index and search embeddings” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

Similar resources

View all

What you get

  • SKILL.md : embedding generation, OpenAI examples and batch processing
  • SKILL.md : index creation, upsert, query and delete with Pinecone

Good fit for

  • You want an assistant to answer from your documents
  • You look for content close in meaning rather than keyword

Not for

    Tags

    • embeddings
    • semantic-search
    • rag
    • vectors

    About

    You say

    “Index the product sheets with embeddings and return the three closest matches to a customer query.”

    Card for the “Index and search embeddings” skill

    Skill published by thelobbi under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to generate embeddings and run semantic search in a vector database
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md6.8 KB

    Origin and licence

    Listed unmodified

    Author
    thelobbi
    Source
    github.com/thelobbi/claude/tree/f971cbfa27f0d1cd9d885bb9ae0f325dbe90dc27/.claude/skills/vector-db
    Licence
    MIT

    Notice

    « vectordb » (thelobbi, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

    User reviews

    –

    No ratings yet

    Loading reviews…

    Delete your review?

    Your rating and comment will be removed from the page.