Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.
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---
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."
license: CC-BY-NC-SA-4.0
metadata:
risk: safe
source: community
date_added: "2026-02-27"
---
# 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.
## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
