qdrant Skill
Vector search engine for production RAG systems. Published by NousResearch in hermes-agent.
Decision snapshot
Is this a fit?
Database workflows, Deployment, Data analysis, Research
Compatibility not yet detected.
Permission behavior not yet detected.
Copy skill directory
29 days ago · MIT license
No specific cautions were detected. Review the source and requested permissions before installing.
What is qdrant Skill?
Vector search engine for production RAG systems. Published by NousResearch in hermes-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Database workflows
- Deployment
- Data analysis
- Research
- Database workflows use cases
Declared skill metadata
- Declared author: Orchestra Research
- Declared license: MIT
- Source file: optional-skills/mlops/qdrant/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use qdrant Skill
- Use it for database workflows.
- Use it for deployment.
- Use it for data analysis.
- Use it for research.
Built with
Editorial notes
Source
- Creator: NousResearch
- Repository: NousResearch/hermes-agent
- Skill file: optional-skills/mlops/qdrant/SKILL.md
What it does
Vector search engine for production RAG systems.
Skill instructions
Qdrant - Vector Similarity Search Engine High-performance vector database written in Rust for production RAG and semantic search. When to use Qdrant Use Qdrant when: - Building production RAG systems requiring low latency - Need hybrid search (vectors + metadata filtering) - Require horizontal scaling with sharding/replication - Want on-premise deployment with full data control - Need multi-vector storage per record (dense + sparse) - Building real-time recommendation systems Key features: - Rust-powered: Memory-safe, high performance - Rich filtering: Filter by any payload field during search - Multiple vectors: Dense, sparse, multi-dense per point - Quantization: Scalar, product, binary for memory efficiency - Distributed: Raft consensus, sharding, replication - REST + gRPC: Both APIs with full feature parity Use alternatives instead: - Chroma: Simpler setup, embedded use cases - FAISS: Maximum raw speed, research/batch processing - Pinecone: Fully managed, zero ops preferred - Weavi
Verified compatibility and discovery
Frequently asked questions
What is qdrant?
qdrant is a open-source AI agent skill with Copy skill directory. Vector search engine for production RAG systems.
Who is qdrant best for?
qdrant is best for reusing agent instructions, scripts, and references, database workflows, deployment workflows, data analysis workflows.
How do I install qdrant?
Install or run qdrant using Copy skill directory. Check qdrant for the latest setup command.
Is qdrant actively maintained?
qdrant may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
