embedding-strategies
Comprehensive guide to embedding models, chunking strategies, and evaluation metrics for vector search and RAG.
Install
npx skills add https://github.com/wshobson/agents --skill embedding-strategiesStats
| Total installs | 3,861 |
| Weekly installs | 3.8K |
| GitHub stars | 32.4K |
| First seen | Jan 20, 2026 |
| Source | @wshobson/agents |
Summary
- Covers 10+ embedding models with dimensions, token limits, and domain specialization (Voyage AI, OpenAI, open-source options for code, finance, legal, and multilingual content)
- Provides four chunking strategies: token-based, sentence-based, semantic sections, and recursive character splitting with overlap handling
- Includes three implementation templates for Voyage AI, OpenAI, and local Sentence Transformers with specialized query/document prefixes
- Features domain-specific pipelines for general documents and code, plus evaluation metrics (precision, recall, MRR, NDCG) for retrieval quality assessment
- Best practices section covers model selection, preprocessing, batching, caching, and common pitfalls
Tags
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FAQ
- How many installs does embedding-strategies have?
- embedding-strategies has 3,861 total installs and 3.8K installs this week.
- Where is embedding-strategies hosted?
- embedding-strategies is published by @wshobson/agents at https://github.com/wshobson/agents.
- How many GitHub stars does embedding-strategies have?
- embedding-strategies has 32.4K GitHub stars.
- When was embedding-strategies first indexed?
- OrangeBot.AI first indexed embedding-strategies on Jan 20, 2026.
- How do I install embedding-strategies?
- Run: npx skills add https://github.com/wshobson/agents --skill embedding-strategies