Embedding Strategies by @wshobson · Skillet

Embedding Strategies

Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.

Permissions

Just instructions. No commands, network, or file access.

Files

SKILL.md

embedding-strategies

Embedding Strategies

Guide to selecting and optimizing embedding models for vector search applications.

When to Use This Skill

Choosing embedding models for RAG
Optimizing chunking strategies
Fine-tuning embeddings for domains
Comparing embedding model performance
Reducing embedding dimensions
Handling multilingual content

Core Concepts

1. Embedding Model Comparison (2026)

Model	Dimensions	Max Tokens	Best For
voyage-3-large	1024	32000	Claude apps (Anthropic recommended)
voyage-3	1024	32000	Claude apps, cost-effective
voyage-code-3	1024	32000	Code search
voyage-finance-2	1024	32000	Financial documents
voyage-law-2	1024	32000	Legal documents
text-embedding-3-large

2 files · 19 KB3 KB

Version history

Document → Chunking → Preprocessing → Embedding Model → Vector
                ↓
        [Overlap, Size]  [Clean, Normalize]  [API/Local]

Embedding Strategies

Embedding Strategies

When to Use This Skill

Core Concepts

1. Embedding Model Comparison (2026)

2. Embedding Pipeline

Templates and detailed worked examples

Best Practices

Do's

Don'ts