rag-implementation
Build Retrieval-Augmented Generation systems with vector databases and semantic search.
🛡️ AgentReady threat assessment
MAESTRO 7-layer threat model + OWASP AIVSS risk score for rag-implementation, derived from its capabilities.
AIVSS 6.7 · Medium
View MAESTRO 7-layer threat model →Overview
An Agent Skill that guides the agent to build RAG pipelines grounding LLM output in external knowledge via vector DBs and semantic search. It covers chunking, embedding, retrieval, and citation to reduce hallucination. The skill injects architecture and code patterns for document Q&A and doc assistants.
Key features
- Vector-DB retrieval and semantic search
- Hallucination reduction via grounding
- Source-citation and chunking patterns
Use cases
- Building document Q&A systems
- Grounding LLMs in proprietary knowledge