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.claude-plugin/plugin.json

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+{
+  "name": "google-gemini-embeddings",
+  "description": "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, integrating",
+  "version": "1.0.0",
+  "author": {
+    "name": "Jeremy Dawes",
+    "email": "jeremy@jezweb.net"
+  },
+  "skills": [
+    "./"
+  ]
+}