google-gemini-embeddings
| 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
View all platforms →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
Works with 14 AI coding assistants
Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/jezweb/claude-skills 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
- search vector
- Market Score
- 47.4
Browse Category
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