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Use this resource to reduce embedding dimensions while keeping good retrieval quality
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Free
In a terminal, from the folder you want:
npx --yes palatekit@latest install matryoshka-embedding-truncationWith 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 loginThe agent checks that the model was trained with MRL, truncates vectors to the chosen dimension and renormalizes them. You get a dimension choice and the storage versus quality trade-off.
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Updated November 2, 2026
You say
“Truncate my OpenAI embeddings to 512 dimensions and measure the recall drop on my test set.”

Skill published by claude-dev-suite under the MIT license, delivered in its original version.
Listed unmodified
« matryoshka-embeddings » (claude-dev-suite, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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