qdrant-vector-search
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
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 nousresearch-hermes-agent-qdrant
Repository
Skill path: skills/mlops/vector-databases/qdrant
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
Open repositoryBest for
Primary workflow: Analyze Data & AI.
Technical facets: Full Stack, Data / AI.
Target audience: Development teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: NousResearch.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install qdrant-vector-search into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/NousResearch/hermes-agent before adding qdrant-vector-search to shared team environments
- Use qdrant-vector-search for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.