Context retrieval layer for AI agents across users' applications. Search and retrieve context from Airweave collections. Airweave indexes and syncs data from user applications to enable optimal contex
Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LL...
Provides answers by retrieving and synthesizing information from local text or markdown files using a retrieval-augmented generation approach.
Build a reusable UI inspiration library that both archives and retrieves design references. Use when the user wants to save screenshots, collect UI inspirati...
--- name: "rag-architect" description: "RAG Architect - POWERFUL" --- # RAG Architect - POWERFUL ## Overview The RAG (Retrieval-Augmented Generation) Architect skill provides comprehensive tools an
Execute Retrieval-Augmented Generation (RAG) using Ragie.ai. Use this skill whenever the user wants to: - Search their knowledge base - Ask questions about u...
Interact with FundraiseUp REST API to manage donations, recurring plans, supporters, campaigns, and donor portal access. Process online and offline donations, retrieve fundraising analytics, and integ
Design and build any search engine with robust indexing, retrieval logic, relevance controls, and evaluation workflows for production systems.
Personal cognitive architecture that learns how you work. Builds a knowledge graph from your sessions, profiles your expertise, adapts retrieval per task, an...
This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. Use this when the user requests earnings calendar data, wants to know which companies ar
Build and deploy local RAG (Retrieval-Augmented Generation) systems with offline document processing, embedding models, and vector storage.
Deterministic memory/context pipeline for agents: route a user message, retrieve relevant memory snippets, compress into a cited Context Pack (sources are sn...
Provides persistent two-tier memory with semantic fact search and raw content retrieval, plus automatic cleanup of temporary session files.
Build RAG (Retrieval Augmented Generation) pipelines with web search and LLMs. Tools: Tavily Search, Exa Search, Exa Answer, Claude, GPT-4, Gemini via OpenRo...
Hybrid document intelligence pipeline ingesting PDFs, images, and spreadsheets with OCR, visual and text search, and field fix capture for fast retrieval.
Lightweight memory management system for OpenClaw with 3-tier retrieval (L0/L1/L2), automatic lifecycle monitoring, and advanced search. Saves 60-80% on toke...
Production-ready long-term memory server for AI agents with Ebbinghaus decay and strength-weighted retrieval. Use when you need persistent memory across agen...
Intelligent search for agents. Multi-source retrieval with confidence scoring - web, academic, and Tavily in one unified API.
Personal knowledge base powered by Ensue for capturing and retrieving understanding. Use when user wants to save knowledge, recall what they know, manage their toolbox, or build on past learnings. Tri
--- name: code-cache description: Semantic code caching for AI agents. Cache, retrieve, and reuse code from prior agent executions. metadata: {"openclaw":{"emoji":"🏄","homepage":"https://raysurfer.