Agent skill

similarity-search-patterns

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

foryourhealth111-pixel2,593★ · 1 repos on radarProfile →
claude-codecodexApache-2.0
Install
npx skills add foryourhealth111-pixel/Vibe-Skills --skill similarity-search-patterns --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 17 KB
Bundled scripts: none
Path: bundled/skills/similarity-search-patterns/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,593
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Similarity Search Patterns Patterns for implementing efficient similarity search in production systems. ## When to Use This Skill - Building semantic search systems - Implementing RAG retrieval - Creating recommendation engines - Optimizing search latency - Scaling to millions of vectors - Combining semantic and keyword search ## Core Concepts ### 1. Distance Metrics | Metric | Formula | Best Fo

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About this skill
What does the similarity-search-patterns skill do?

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

How do I install it?

Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill similarity-search-patterns --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From foryourhealth111-pixel/Vibe-Skills, a repository with 2,593 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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