similarity-search-patterns
Implement efficient similarity search with vector databases
Install / Use
npx skills add wshobson/agents --skill similarity-search-patternsInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Data & AnalyticsSupported Platforms
Our assessment of similarity-search-patterns
similarity-search-patterns scores 79/100 on our quality scale, 151st of 219 Data & Analytics skills we index.
Its SKILL.md is 2.3 KB long, well organised into 9 sections with 1 code example: moderately detailed.
With 39,920 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 5 days ago, so similarity-search-patterns is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
similarity-search-patterns compared with similar skills
All 4 of these similar skills score higher than similarity-search-patterns; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| similarity-search-patterns (this skill)by wshobson | 79 | 39.9k | 5d ago | SKILL.md |
| algorithmic-artby anthropics | 100 | 177.9k | 4d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 4d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 5d ago | SKILL.md |
| ui-ux-pro-maxby nextlevelbuilder | 100 | 130.2k | 5d ago | SKILL.md |
Frequently asked questions
- How do I install similarity-search-patterns?
- Run
npx skills add wshobson/agents --skill similarity-search-patterns. The install tabs above show the steps for each supported agent. - Which AI agents does similarity-search-patterns work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is similarity-search-patterns safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is similarity-search-patterns still maintained?
- The repository was last updated 5 days ago, so similarity-search-patterns is actively maintained.
Skill content
View source on GitHubname: 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.
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
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
