MarketplaceSKILL.mdLeída en 46891e7
similarity-search-patterns
Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.
Resumen
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 |
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
Archivos 2 archivos
Instálala a mano
Deska ejecuta esto por ti, para cada agente que elijas. Para ejecutarlo tú en una terminal:
npx skills add wshobson/agents --skill similarity-search-patternsMás de wshobson
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