pinecone
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.
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 orchestra-research-ai-research-skills-pinecone
Repository
Skill path: 15-rag/pinecone
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.
Open repositoryBest for
Primary workflow: Analyze Data & AI.
Technical facets: Full Stack, Backend, Data / AI.
Target audience: Development teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: Orchestra-Research.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install pinecone into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/Orchestra-Research/AI-Research-SKILLs before adding pinecone to shared team environments
- Use pinecone for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.