Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.
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---
version: 4.1.0-fractal
name: similarity-search-patterns
description: Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.
---
# Similarity Search Patterns
Patterns for implementing efficient similarity search in production systems.
## Use this skill when
- Building semantic search systems
- Implementing RAG retrieval
- Creating recommendation engines
- Optimizing search latency
- Scaling to millions of vectors
- Combining semantic and keyword search
## Do not use this skill when
- The task is unrelated to similarity search patterns
- You need a different domain or tool outside this scope
## Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open `resources/implementation-playbook.md`.
## Resources
- `resources/implementation-playbook.md` for detailed patterns and examples.
## 🧠 Knowledge Modules (Fractal Skills)
### 1. [implementation-playbook](./sub-skills/implementation-playbook.md)
