similarity-search-patterns
Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.
How do I install this agent skill?
npx skills add https://github.com/wshobson/agents --skill similarity-search-patternsIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill provides implementation templates for similarity search with various vector databases such as Pinecone, Qdrant, PostgreSQL, and Weaviate. No malicious patterns, such as prompt injection, data exfiltration, or unauthorized remote code execution, were identified. The code uses standard, reputable libraries and follows common development patterns.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
- Runlayerpass
1/1 file flagged
- ZeroLeakspass
Score: 93/100 · 2 sections analyzed
What does this agent skill do?
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 For | | ------------------ | ------------------ | --------------------- | --- | -------------- | | 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 |
2. Index Types
┌─────────────────────────────────────────────────┐
│ Index Types │
├─────────────┬───────────────┬───────────────────┤
│ Flat │ HNSW │ IVF+PQ │
│ (Exact) │ (Graph-based) │ (Quantized) │
├─────────────┼───────────────┼───────────────────┤
│ O(n) search │ O(log n) │ O(√n) │
│ 100% recall │ ~95-99% │ ~90-95% │
│ Small data │ Medium-Large │ Very Large │
└─────────────┴───────────────┴───────────────────┘
Templates and detailed worked examples
Full template library and detailed worked examples live in references/details.md. Read that file when you need the concrete templates.
Best Practices
Do's
- Use appropriate index - HNSW for most cases
- Tune parameters - ef_search, nprobe for recall/speed
- Implement hybrid search - Combine with keyword search
- Monitor recall - Measure search quality
- Pre-filter when possible - Reduce search space
Don'ts
- Don't skip evaluation - Measure before optimizing
- Don't over-index - Start with flat, scale up
- Don't ignore latency - P99 matters for UX
- Don't forget costs - Vector storage adds up
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/wshobson/agents/similarity-search-patterns">View similarity-search-patterns on skillZs</a>