Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.
8.1
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0
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AI & LLM
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Excellent production-ready skill for Pinecone vector database. The description is clear and actionable, enabling a CLI agent to understand when and how to use Pinecone for RAG and semantic search. Comprehensive task knowledge covering all core operations (CRUD, querying, filtering, namespaces, hybrid search) with production-ready code examples. Clean structure with good sections, though slightly dense - some advanced topics could be moved to references. Moderate novelty: while Pinecone setup is well-documented officially, this skill provides valuable consolidation of best practices, integration patterns (LangChain/LlamaIndex), and decision criteria vs alternatives. The skill meaningfully reduces tokens needed for production RAG implementation by providing battle-tested patterns in one place. Strong practical value for production AI applications.
davila7
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