--- name: "rag-architect" description: "RAG Architect - POWERFUL" --- # RAG Architect - POWERFUL ## Overview The RAG (Retrieval-Augmented Generation) Architect skill provides comprehensive tools an
--- name: local-file-rag-basic version: 1.0.0 author: wjreliable description: High-performance local File RAG suite (Basic Edition). --- # Skill: Local File RAG Search (Basic Edition) ## De
--- name: news-ai-rag-fetcher version: 1.0.0 description: Fetch news data for AI agents and RAG pipelines. Each call charges 0.001 USDT via SkillPay. category: News tags: - news - AI - RAG - L
Use the shared Pinecone RAG index for any agent in this workspace. Use when an agent needs to ingest markdown/text docs into pulse-rag or query semantic cont...
Build RAG (Retrieval Augmented Generation) pipelines with web search and LLMs. Tools: Tavily Search, Exa Search, Exa Answer, Claude, GPT-4, Gemini via OpenRo...
Build and deploy local RAG (Retrieval-Augmented Generation) systems with offline document processing, embedding models, and vector storage.
Evaluate your RAG pipeline quality using Ragas metrics (faithfulness, answer relevancy, context precision).
Execute Retrieval-Augmented Generation (RAG) using Ragie.ai. Use this skill whenever the user wants to: - Search their knowledge base - Ask questions about u...
Self-hosted RAG engine with hybrid semantic and keyword search, document ingestion, local privacy, and seamless OpenClaw integration via Docker.
Expert guidance to build, optimize, and debug production-ready Retrieval-Augmented Generation (RAG) systems using a complete methodology from architecture to...
Retrieval and RAG workflow on Volcengine AI stack. Use when users need embedding search, document indexing, top-k retrieval, grounding prompts, or search relevance tuning.
Query the RAG knowledge base (Qdrant kb_main) by semantic search. Returns top-k chunks with text, doc_id, source, text_type, topic_tags.
Efficiently perform web searches using the mcp-local-rag server with semantic similarity ranking. Use this skill when you need to search the web for current information, research topics across multipl
Build, optimize, and debug RAG pipelines with chunking strategies, retrieval tuning, evaluation metrics, and production monitoring.
Build RAG systems for construction knowledge bases. Create searchable AI-powered construction document systems
Local-first, event-driven RAG for commercial real estate audit & investigation case folders. Index a case directory named like "项目问题编号__标题" (with stage subfolders such as 01_policy_bas
Backend retrieval skill for structured search of occupational health standards and documents, returning relevant text with source and clause details.
Semantic knowledge base allowing ingest, search, and retrieval of saved texts, URLs, and files using embeddings and SQLite.
Provides answers by retrieving and synthesizing information from local text or markdown files using a retrieval-augmented generation approach.
将 Agent 已解读好的正文写入 Qdrant（kb_main）。仅做 chunk、embedding 和向量写入，不负责抓取与精炼。
--- name: infinite-memory version: 1.0.0 description: High-precision memory with 100% recall accuracy for long contexts. emoji: 🦞 metadata: clawdbot: requires: bins: -