embedding-strategies

version: 4.1.0-fractal name: embedding-strategies description: 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.

Embedding Strategies

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

Do not use this skill when

• The task is unrelated to embedding strategies
• You need a different domain or tool outside this scope

Instructions

• Clarify goals, constraints, and required inputs.
• Apply relevant best practices and validate outcomes.
• Provide actionable steps and verification.
• If detailed examples are required, open resources/implementation-playbook.md.

Use this skill when

• 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

🧠 Knowledge Modules (Fractal Skills)

1. 1. Embedding Model Comparison

2. 2. Embedding Pipeline

3. Template 1: OpenAI Embeddings

4. Template 2: Local Embeddings with Sentence Transformers

5. Template 3: Chunking Strategies

6. Template 4: Domain-Specific Embedding Pipeline

7. Template 5: Embedding Quality Evaluation

8. Do's

9. Don'ts