Skills tagged: rag

• qa-tester - Fully autonomous QA testing agent for Modular RAG MCP Server

  qa-testingmcp-serverragtest-automation

  ★ 0 · Updated 2026-09-23

  Executes autonomous QA tests for Modular RAG MCP Server, diagnoses failures, applies fixes, and records progress.

  ⚙ Execute CLI test commands⚙ Test Dashboard UI via AppTest⚙ Test MCP protocol via JSON-RPC
• qa-tester - Automated QA testing agent for Modular RAG MCP Server

  qa-testingmcp-serverautomated-testingrag

  ★ 1 · Updated 2026-09-23

  Executes test cases, diagnoses failures, applies fixes with up to 3 retry rounds, and records results for Modular RAG MCP Server.

  ⚙ Execute automated QA test cases⚙ Diagnose test failures⚙ Apply minimal code fixes
• qa-tester - Autonomous QA testing agent for Modular RAG MCP Server.

  qatestingmcp-serverrag

  ★ 0 · Updated 2026-09-23

  Executes automated CLI, UI, and MCP protocol tests, diagnoses failures, applies code fixes, and updates QA test progress.

  ⚙ Execute CLI test commands⚙ Execute Dashboard UI AppTests⚙ Execute MCP JSON-RPC tests
• agent-architecture-expert - Architectural design guide for agentic systems and RAG.

  agent-architectureragaws-bedrocktool-design

  ★ 1 · Updated 2026-09-22

  Provides design patterns, RAG pipelines, tool interface guidelines, memory systems, and AWS Bedrock Agents integration.

  ⚙ Design agentic system architectures⚙ Build RAG search pipelines⚙ Configure AWS Bedrock Agents
• AgentDB Vector Search - Semantic vector search with AgentDB

  vector-searchagentdbsemantic-searchrag

  ★ 2 · Updated 2026-09-20

  Implements vector-based semantic search using AgentDB for document retrieval, similarity matching, and context-aware querying.

  ⚙ Initialize vector database⚙ Query vector database⚙ Export vectors to JSON
• langchain - Build LLM applications using LangChain.

  langchainlcelragagent

  ★ 76 · Updated 2026-09-20

  Build LLM applications using LCEL chains, RAG pipelines, and LangGraph agents.

  ⚙ Build LCEL chains⚙ Implement RAG pipelines⚙ Create LangGraph agents
• llm-application-dev-langchain-agent - LangChain & LangGraph Agent Development Expert

  langchainlanggraphagentrag

  ★ 0 · Updated 2026-09-19

  Provides architecture guidance and implementations for production-grade AI agents using LangChain 0.1+ and LangGraph.

  ⚙ Design LangGraph state graphs⚙ Implement async RAG pipelines⚙ Configure agent memory systems
• ai-engineer - Build production-ready LLM applications and AI agents

  aillmragagent

  ★ 0 · Updated 2026-09-19

  Develops production-ready LLM applications, advanced RAG systems, vector search, multimodal AI, and agent orchestration.

  ⚙ Build LLM applications⚙ Implement RAG systems⚙ Orchestrate multi-agent workflows
• ai-engineer - Build production LLM applications, RAG, and AI agents.

  llmragai-agentsvector-search

  ★ 0 · Updated 2026-09-19

  Implements LLM applications, RAG systems, vector search, agent orchestration, multimodal AI, and enterprise AI integrations.

  ⚙ Integrate LLM models and serving frameworks⚙ Build multi-stage retrieval RAG pipelines⚙ Orchestrate multi-agent workflows and memory
• ai-engineer - AI Engineer for LLM Applications, RAG, and AI Agents

  llmragai-agentsvector-search

  ★ 1 · Updated 2026-09-19

  Builds production-ready LLM applications, advanced RAG systems, intelligent agents, and multimodal AI integrations.

  ⚙ Integrate LLM models and serving frameworks⚙ Build advanced RAG systems⚙ Orchestrate multi-agent workflows and memory
• fde-kb - FDE Knowledge Base (Obsidian + sqlite-vec)

  obsidianknowledge-basevector-searchsqlite-vec

  ★ 0 · Updated 2026-09-19

  Perform local search, note lookup, ingestion, and evaluation over the team's Obsidian knowledge base vault.

  ⚙ Search Obsidian vault notes⚙ Read vault note content⚙ Ingest new note into vault
• cx-conversation-embedding-pipeline - Design a support conversation vectorisation pipeline

  vector-searchsemantic-searchembedding-pipelinesupport-data

  ★ 1 · Updated 2026-09-18

  Designs a pipeline that vectorises support conversations for semantic search while managing chunking, PII redaction, and deletion.

  ⚙ Chunk conversations on turn boundaries⚙ Attach metadata filters to vectors⚙ Redact PII prior to embedding
• experiments-index - Incrementally append records to FAISS and HuggingFace store

  faisshuggingface-datasetsvector-storeincremental-append

  ★ 2 · Updated 2026-09-18

  Appends campaign result records to an existing FAISS index and HuggingFace dataset under an fcntl file lock.

  ⚙ Acquire exclusive fcntl file lock⚙ Embed text records with encoder⚙ Normalize embeddings using L2 norm
• llm-architect - LLM System Architecture and Optimization

  llmarchitectureragfine-tuning

  ★ 602 · Updated 2026-09-17

  Designs scalable large language model applications with a focus on performance, cost efficiency, and safety.

  ⚙ Design end-to-end LLM systems⚙ Select models and serving infrastructure⚙ Implement RAG pipelines
• rag-expert - RAG Knowledge Base Management Expert

  ragknowledge-basellamaindexzhipu-ai

  ★ 14 · Updated 2026-09-17

  Provides RAG knowledge base management including document uploading, vector indexing, semantic search, and document maintenance using LlamaIndex and ZhiPu AI.

  ⚙ Upload document to knowledge base⚙ Query knowledge base semantically⚙ List imported documents
• building-with-llms - Help users build effective AI applications using LLMs

  llmai-applicationspromptingrag

  ★ 18 · Updated 2026-09-16

  Provides practical techniques for building AI applications, writing prompts, implementing RAG, creating agents, and running evals.

  ⚙ Understand user AI use cases⚙ Diagnose AI application problems⚙ Apply prompting and architecture techniques
• code-refactoring-context-restore - Context Restoration: Advanced Semantic Memory Rehydration

  context-restorationsemantic-memorycode-refactoringrag

  ★ 0 · Updated 2026-09-16

  Recover and reconstruct project context across distributed AI workflows.

  ⚙ Recover and reconstruct project context⚙ Retrieve context vectors semantically⚙ Rank context components by relevance
• rag-expert - Retrieval-Augmented Generation Patterns on OCI

  ragocioracle-cloudvector-search

  ★ 0 · Updated 2026-09-16

  Provides architecture patterns, model selection, vector store options, and retrieval optimization guidance for RAG on Oracle Cloud Infrastructure.

  ⚙ Design RAG architectures on OCI⚙ Select embedding models and vector stores⚙ Optimize retrieval and hybrid search
• rag-expert - RAG Expert for Oracle Cloud Infrastructure

  ragocioracle-cloudvector-search

  ★ 1 · Updated 2026-09-16

  Provides patterns and guidance for building production RAG systems on Oracle Cloud Infrastructure.

  ⚙ Design enterprise RAG architectures⚙ Select embedding models and vector stores⚙ Optimize retrieval quality
• rag-architect - Design, tune, and evaluate production RAG pipelines

  ragretrievalchunkingembedding

  ★ 1 · Updated 2026-09-15

  Design RAG pipelines, optimize chunking strategies, select embedding models and vector databases, and evaluate retrieval quality metrics.

  ⚙ Analyze corpus chunking strategies⚙ Design RAG pipeline configurations⚙ Evaluate retrieval quality metrics

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