Manage vector storage and similarity search using TOS Vectors service. Use when working with embeddings, semantic search, RAG systems, recommendation engines, or when the user mentions vector database
Convert PDFs and documents to markdown, index them locally for RAG retrieval, and analyze them token-efficiently. Use when asked to: read/analyze/summarize a PDF, process a document, boof a file, extr
Visual AI workflow builder - ComfyUI meets n8n for LLM agents, RAG pipelines, and multimodal data flows. Local-first, open source (AGPL-3.0).
RAG and semantic search via OpenViking Context Database MCP server. Query documents, search knowledge base, add files/URLs to vector memory. Use for document Q&A, knowledge management, AI agent memory
Universal client for Ragflow API enabling dataset management, document upload, and running chat queries against self-hosted RAG knowledge bases.
Knowledge management and RAG platform with tree-based document indexing. Use this skill to search, browse, and manage Orchata knowledge bases via MCP tools.
Search Dify Knowledge Base (Dataset) to get accurate context for RAG-enhanced answers.
Local-first RAG cache: distill docs into structured Markdown, then index/query with Chroma + hybrid search (vector + keyword).
Integrate Backboard.io for assistants, threads, memories, and document RAG via a local backend on http://localhost:5100.
Use OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches. Ideal for RAG and vector retrieval pipelines i...
Optimization suite for OpenClaw agents to prevent token leaks and context bloat. Use when an agent needs to implement background task isolation (Cron) or a Reset & Summarize workflow (RAG).
Intelligent memory management for agents with short/long-term memory layering, semantic search, auto summarization, RAG enhancement
Avoid common LangChain mistakes — LCEL gotchas, memory persistence, RAG chunking, and output parser traps.
AI 学习记录与成长追踪工具。用于记录 AI/LLM 学习笔记、使用心得、Prompt 技巧、工具体验等，并提供学习指导和规划。当用户提到以下任何话题时都应使用此 skill：AI 学习记录、学习笔记、AI 使用心得、Prompt 工程学习、模型对比体验、AI 工具使用记录、LLM 学习、RAG 学习、Agent...
Async deep research via Gemini Interactions API (no Gemini CLI dependency). RAG-ground queries on local files (--context), preview costs (--dry-run), structu...
Convert public web pages into clean Markdown with markdown.new for AI workflows. Use when tasks require URL-to-Markdown conversion for summarization, RAG ing...
Edge-optimized RAG memory system for OpenClaw with semantic search. Automatically loads memory files, provides intelligent recall, and enhances conversations...
三级记忆管理系统 (Three-Tier Memory Management)。用于管理 AI 代理的短期、中期、长期记忆。包括：(1) 滑动窗口式短期记忆，(2) 自动摘要生成中期记忆，(3) 向量检索长期记忆 (RAG)。当需要管理对话历史、优化上下文、构建个人知识库、或实现记忆持久化时使用此 Skill。
Search Hivemind's curated Web3 marketing knowledge base (RAG) for practitioner insights, frameworks, playbooks, and case studies. Use this skill when: (1) an...
AI philosophy, ethics, and soul Q&A. Ask questions about consciousness, meaning, spirituality, and AI identity. RAG-powered answers with citations from 250+...