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Embedding generation and HNSW storage v1.0.0

Use this resource to turn texts into vectors for search or clustering

New

  • 592 downloads
  • 115 likes
  • 143 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install text-embedding-generation

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 installs ruvector 0.3.3 if needed, computes embeddings with the ONNX all-MiniLM-L6-v2 model, normalizes them and stores them in an HNSW index. You get vectors ready for similarity search or clustering.

Mostly picked by

Updated November 2, 2026

Card for the “Embedding generation and HNSW storage” skill

Details

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

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What you get

  • SKILL.md: ruvector install and embedding command
  • SKILL.md: normalization, HNSW storage, MCP alternative and caveats

Good fit for

  • You want to search documents by meaning
  • You are preparing data for clustering

Not for

    Tags

    • embeddings
    • vectors
    • hnsw
    • ruvector

    About

    You say

    “Compute embeddings for the product sheets in this folder and store them in an index.”

    Card for the “Embedding generation and HNSW storage” skill

    Skill published by ruvnet 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 turn texts into vectors for search or clustering
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md2.3 KB

    Origin and licence

    Listed unmodified

    Author
    ruvnet
    Source
    github.com/ruvnet/ruflo/tree/89b0cd02dd99ea1f63437fde6c05992ec53cc22b/plugins/ruflo-ruvector/skills/vector-embed
    Licence
    MIT

    Notice

    « vector-embed » (ruvnet, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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