Improve Qdrant vector search relevance and retrieval quality

Use Qdrant's official qdrant-search-quality skill when an agent needs to diagnose weak recall, irrelevant matches, or embedding and chunking mistakes in a live retrieval pipeline. It is a bounded search-quality tuning workflow, not a generic database listing.

Installation

Use the upstream install or setup path that matches your environment:

• npx skills add qdrant/skills

Requirements and caveats from upstream:

• "I have 50M vectors on a single node and search is slow, should I add more nodes?"
• | qdrant-clients-sdk | SDK setup, code examples, snippet search across Python, TypeScript, Rust, Go, .NET, Java |

Basic usage or getting-started notes:

• npx skills

• bash

• Claude Code

• Source: https://github.com/qdrant/skills/tree/main/skills/qdrant-search-quality

• Extracted from upstream docs: https://raw.githubusercontent.com/qdrant/skills/HEAD/README.md

Documentation

• https://github.com/qdrant/skills/tree/main/skills/qdrant-search-quality

Source

• Agent Skill Exchange