embedding-strategies
Guide to selecting and optimizing embedding models for vector search applications.
npx skills add majiayu000/claude-skill-registry --skill embedding-strategies-sickn33-antigravity-awesome --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 ### 1. Embedding Model Comparison | Model | Dimensions | Max Tokens | Best For | |-------|------------|------------|----------| | **text-embedding-3-large** | 3072 | 8191 | High accuracy | | **text-embedding-3-small** | 1536 | 8191 | Cost-effective | | **voyage-2** | 1024 | 4000 | Code, legal | | **bge-large-en-v1.5** | 1024 | 512 | Open source | | **all-MiniLM-L6-v2** | 384 | 256 | Fast, lightweight | | **multilingual-e5-large** | 1024 | 512 | Multi-langu
- Do not use this skill when
- Instructions
- Use this skill when
- Core Concepts
- 1. Embedding Model Comparison
- 2. Embedding Pipeline
- Templates
- Template 1: OpenAI Embeddings
- Template 2: Local Embeddings with Sentence Transformers
- Template 3: Chunking Strategies
- Template 4: Domain-Specific Embedding Pipeline
- Template 5: Embedding Quality Evaluation
- Best Practices
- Do's
What does the embedding-strategies skill do?
Guide to selecting and optimizing embedding models for vector search applications.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill embedding-strategies-sickn33-antigravity-awesome --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.