qdrant-vector-search SKILL.md skillA
qdrant-vector-search from orchestra-research/ai-research-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add orchestra-research/ai-research-skills/qdrant-vector-search@v1.0.0Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- orchestra-research/ai-research-skills
- Path
15-rag/qdrant/SKILL.md- Versions recorded
- 1
- Latest version
- v1.0.0, committed Nov 25, 2025
- Size
- 13,451 bytes
- Repository stars
- 13,718
- License
- MIT
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.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# 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 - **Weaviate**: GraphQL preference, built-in vectorizers ## Quick start ### Installation ```bash # Python client pip install qdrant-client …
Read the whole file at its exact version.
How to install
mdr add orchestra-research/ai-research-skills/qdrant-vector-search@sha256:3a45489baf49c375The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_q4btwxpjdv46wkiw)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Nov 25, 2025.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (13451 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
orchestra-research/ai-research-skills · 13,718 stars · license MIT · pushed 2026-10-11 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_q4btwxpjdv46wkiw GET https://markdownregistry.com/api/v1/resolve?ref=orchestra-research/ai-research-skills/qdrant-vector-search GET https://markdownregistry.com/api/v1/blob/3a45489baf49c375883694ec78d6a9b283533a352e8d47cf630332faff83a231
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.