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Embedding Index Tuner

Agent skill
1 skill

Tune a vector index — HNSW graph parameters and quantization — to hit a recall target at the lowest latency and memory, by sweeping settings against a fixed query set instead of trusting defaults. Use when vector search is slow or memory-hungry, when recall dropped after enabling quantization, or when standing up an index and you need defensible parameters.

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

Supported by the Atlas install prompt. Skill-specific requirements vary.

Skill stats

Skills1CategoryGeneralStars0

About this skill

Tune a vector index — HNSW graph parameters and quantization — to hit a recall target at the lowest latency and memory, by sweeping settings against a fixed query set instead of trusting defaults. Use when vector search is slow or memory-hungry, when recall dropped after enabling quantization, or when standing up an index and you need defensible parameters.

Quick start

  1. Copy the install prompt. Use the green button above this README.
  2. Send it to your agent. Paste it into your coding agent’s chat and send.
  3. Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.
Review, license & listing details
Review the source before using this skill

This is an imported listing. We haven’t certified its safety, license, or compatibility. Skills may include executable scripts.

Automated security scan: Partial

Only SKILL.md was scanned. Supporting files and scripts were not checked. No safety grade has been assigned.

0 potential findings · Scanned 11/4/2026 · Scanner 0.2.1

Content SHA-256: 808cdc2fa90dc825aa020eb2f508e20ebf01d906e6a9c321fb9de9c3e93fadb1

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About this listing

Category
General
Reported license
MIT
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Embedding Index Tuner | Agent Skills Atlas