google-gemini-embeddings

47

| Build RAG systems, semantic search, and document clustering with Gemini embeddings API (gemini-embedding-001). Generate 768-3072 dimension embeddings for vector search, integrate with Cloudflare Vectorize, and use 8 task types (RETRIEVAL_QUERY, RETRIEVAL_DOCUMENT, SEMANTIC_SIMILARITY) for optimized retrieval. Use when: implementing vector search with Google embeddings, building retrieval-augmented generation systems, creating semantic search features, clustering documents by meaning, integrati

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Installation for Agentic Skill

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skilz install jezweb/claude-skills/google-gemini-embeddings
skilz install jezweb/claude-skills/google-gemini-embeddings --agent opencode
skilz install jezweb/claude-skills/google-gemini-embeddings --agent codex
skilz install jezweb/claude-skills/google-gemini-embeddings --agent gemini

First time? Install Skilz: pip install skilz

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Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/jezweb/claude-skills
2. Copy the agent skill directory:
cp -r claude-skills/skills/google-gemini-embeddings ~/.claude/skills/

Need detailed installation help? Check our platform-specific guides:

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Agentic Skill Details

Repository
claude-skills
Type
Non-Technical
Meta-Domain
general
Primary Domain
general
Sub-Domain
database search vector
Market Score
47

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