google-gemini-embeddings
Build RAG systems and semantic search with Gemini embeddings (gemini-embedding-001). 768-3072 dimension vectors, 8 task types, Cloudflare Vectorize integration. Prevents 13 documented errors. Use when: vector search, RAG systems, semantic search, document clustering. Troubleshoot: dimension mismatch, normalization required, batch ordering bug, memory limits, wrong task type, rate limits (100 RPM).
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install jezweb-claude-skills-google-gemini-embeddings
Repository
Skill path: skills/google-gemini-embeddings
Build RAG systems and semantic search with Gemini embeddings (gemini-embedding-001). 768-3072 dimension vectors, 8 task types, Cloudflare Vectorize integration. Prevents 13 documented errors. Use when: vector search, RAG systems, semantic search, document clustering. Troubleshoot: dimension mismatch, normalization required, batch ordering bug, memory limits, wrong task type, rate limits (100 RPM).
Open repositoryBest for
Primary workflow: Analyze Data & AI.
Technical facets: Full Stack, Data / AI, Integration.
Target audience: Development teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: jezweb.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install google-gemini-embeddings into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/jezweb/claude-skills before adding google-gemini-embeddings to shared team environments
- Use google-gemini-embeddings for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.