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Vector similarity search v1.0.0

Use this resource to implement nearest-neighbour search in a vector database

New

  • 574 downloads
  • 200 likes
  • 150 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install vector-similarity-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 chooses the distance metric (cosine, Euclidean and so on) and the index type that fit your volume and latency. It also advises on combining semantic and keyword search.

Mostly picked by

Updated November 2, 2026

Card for the “Vector similarity search” skill

Details

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

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What you get

    Good fit for

    • You are building semantic search or a RAG system
    • Your vector search slows down with millions of vectors

    Not for

      Tags

      • vectors
      • semantic search
      • index
      • embeddings

      About

      You say

      “Propose a vector search strategy for a catalogue of two million products.”

      Card for the “Vector similarity search” skill

      Skill published by wshobson 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 implement nearest-neighbour search in a vector database
      3. Review and adjust the result

      Content preview

      Files

      • LICENSE1.1 KB
      • NOTICE-PALATEKIT.md0.5 KB
      • references/details.md15.5 KB
      • SKILL.md2.8 KB

      Origin and licence

      Listed unmodified

      Author
      wshobson
      Source
      github.com/wshobson/agents/tree/0874a27b17a22e2b7c2e2bcd725768e0803cad06/plugins/llm-application-dev/skills/similarity-search-patterns
      Licence
      MIT

      Notice

      « similarity-search-patterns » (wshobson, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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