semantic-search

SKILL.md

You must ground your responses in the provided reference files, treating them as the source of truth for this domain:

Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.

Build production-ready semantic search systems using vector databases, embeddings, and retrieval-augmented generation (RAG). Covers vector DB selection (Pinecone/Qdrant/Weaviate), embedding models (OpenAI/Voyage/Cohere), chunking strategies, hybrid search, and reranking for high-quality retrieval. Use when ", vector-search, embeddings, rag, pinecone, qdrant, weaviate, llama-index, langchain, hybrid-search, reranking" mentioned. Source: omer-metin/skills-for-antigravity.

Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/omer-metin/skills-for-antigravity --skill semantic-search Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor

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