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Vector Distance Metrics

Agent skill
1 skill

Vector similarity and distance algorithms for agent memory ranking. Cosine similarity, Euclidean distance, Manhattan distance, Jaccard, Hamming, and when to use each metric for different embedding types. Sources: mljs/distance.

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

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

Skill stats

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About this skill

Vector similarity and distance algorithms for agent memory ranking. Cosine similarity, Euclidean distance, Manhattan distance, Jaccard, Hamming, and when to use each metric for different embedding types. Sources: mljs/distance.

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
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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: b94e4e26145129021a8fd4556354eafbb41a74e23b821a8d1448a6bc66bc010f

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About this listing

Category
General
Reported license
Not specified
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.
Vector Distance Metrics | Agent Skills Atlas