similarity-search-patterns

SKILL.md

Patterns for implementing efficient similarity search in production systems.

| Cosine | 1 - (A·B)/(‖A‖‖B‖) | Normalized embeddings | | Euclidean (L2) | √Σ(a-b)² | Raw embeddings | | Dot Product | A·B | Magnitude matters | | Manhattan (L1) | Σ | a-b | | Sparse vectors |

Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance. Source: wshobson/agents.

Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/wshobson/agents --skill similarity-search-patterns Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor

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