“RAG”

Build RAG (Retrieval-Augmented Generation) agents with Google ADK and Vertex AI RAG Engine.

Local-first RAG engine with MCP server for AI agent integration.

Use when comparing basic, enhanced, GraphRAG, or agentic RAG designs, evaluating domain-specific RAG quality, tuning retrieval components, or deciding whether…

Triggers on keywords RAG, GraphRAG, vector database, agentic RAG, semantic search

Use when needing global or relational understanding of codebases or knowledge corpora.

Vertex AI RAG Engine integration patterns for grounding agent responses in private data sources including corpus management, retrieval tool creation, and…

Local-first agentic RAG with citations - hybrid search, reranking, multimodal document retrieval

Use this skill when you need evidence-bounded grounding, relevance, completeness, citation support, abstention, and answer-level evidence in RAG outputs…

RAG 模式 —— 检索增强生成架构设计、分块策略、向量检索优化与评估方法

Agentic RAG 检索、查询改写、证据判断与引用规则

Query a RAG (Retrieval-Augmented Generation) knowledge base to find relevant information from ingested documents.

Use quando precisar buscar contexto vetorial, gerar embeddings, ou consultar o RAG.

RAG pipeline design — chunking, embeddings, retrieval strategies, evaluation, and demo patterns.

Systematic evaluation of Retrieval-Augmented Generation (RAG) pipelines measuring faithfulness, answer relevance, context recall, and precision.

Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search…

RAG (Retrieval-Augmented Generation) system for affidavit workflows.

Detect persistent-memory poisoning and RAG/knowledge-base contamination via dialogue testing.

Use for RAG, vector search, semantic search, embeddings, knowledge bases, long-term agent memory, and grounding answers in the project's own documentation.

Long-term memory via Hermes workspace RAG — ingest notes, index, search, family cards, digests, reports.

Runs checklists and workflows for designing, layering, evaluating, and operating production RAG and AI search — hybrid retrieval, agentic context tools…

对话时的角色 system prompt（问答与选定文章摘要共用；引用硬性规则由系统在问答时自动追加）

当用户询问工业设备维修、故障排查、故障代码、操作规范、设备型号、异常报警等问题时使用。必须调用企业内网 RAG 知识库获取权威答案，严禁凭预训练记忆编造故障代码或维修步骤。

Runs workflows for AIEWF 2024 RAG talks — layout-aware ingest, GraphRAG, eval-driven tuning, Pydantic structured IO, MongoDB vectors, EMT memory, construction…

RAG setup with Elasticsearch as the retrieval backend