Qdrant · Retrieval-augmented generation

Explains how to run Qdrant, a Rust vector database, for RAG and semantic search, covering collections, points, distance metrics and filtered or batched queries.

Orchestra-Research/AI-Research-SKILLs

Diagnose, troubleshoot, and advise on any Qdrant deployment by loading the latest official Qdrant skills live from skills.qdrant.tech.

qdrant/skills

Guides Qdrant search strategy selection. An agent skill from qdrant/skills.

qdrant/skills

Build retrieval-augmented generation systems: pick a vector database and embedding model, choose retrieval and reranking strategies, and start from a LangGraph pipeline.

wshobson/agents

Designs retrieval-augmented generation systems: document chunking, embeddings, vector store setup, hybrid search, reranking and retrieval evaluation, with checks at each step.

Jeffallan/claude-skills

Hunt vector-store / embedding-layer weaknesses in RAG pipelines (OWASP LLM08 Vector and Embedding Weaknesses) — persistent corpus poisoning that survives across sessions and users (distinct from…

elementalsouls/Claude-BugHunter

Vector database implementation for AI/ML applications, semantic search, and RAG systems.

ancoleman/ai-design-components

Guides Qdrant search strategy selection. An agent skill from github/awesome-copilot.

github/awesome-copilot

Diagnoses and improves Qdrant search relevance. An agent skill from github/awesome-copilot.

github/awesome-copilot

Security-first SOP for multi-tenant RAG systems. An agent skill from agentsope/SkillAlchemy.

agentsope/SkillAlchemy

Vector search engine for production RAG systems. An agent skill from Luciole-Studio/Misaka-Agent.

Luciole-Studio/Misaka-Agent

Expanding the candidate pool via relevance feedback, as an alternative to reranking when a dense retriever is too weak.

qdrant/skills

Guides building on Qdrant Edge, the embedded in-process shard.

qdrant/skills

Explains hybrid search in Qdrant. An agent skill from qdrant/skills.

qdrant/skills

Fusing scores from multiple searches into a single ranked result (RRF, DBSF, custom fusion).

qdrant/skills

Constructing prefetch queries for hybrid retrieval, including sparse/dense and multi-field setups, and choosing a sparse embedding model.

qdrant/skills

Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+).

neo4j-contrib/neo4j-skills

RAG: embeddings, chunking, hybrid search (BM25+vector), reranking, CRAG, multi-hop.

softspark/ai-toolkit

Diagnoses and improves Qdrant search relevance. An agent skill from qdrant/skills.

qdrant/skills

Build production RAG systems with semantic chunking, incremental indexing, and filtered retrieval.

aiskillstore/marketplace