Generate AI dream sequences from previous day's memories for cross-model reflection and introspection
Semantic search tool to quickly find answers across multiple code repositories with AI memory of your preferences for faster documentation lookup.
Wave-based hyperdimensional memory system with multi-agent swarm synchronization. Memories resonate with amplitude, frequency, phase, and decay — fading thro...
Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vibe-coding ready.
Monitors AI coding agents to track dependency choices, classify discovery methods, flag risks, and reveal biases and missed alternatives in your project.
Obsidian lecture notes with recursive atomic decomposition. Generates main note (hub), atomic notes (3+ layers deep, rich structure each), and unlimited glos...
Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions.
Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vib...
Fast semantic memory system with JSON indexing, auto-consolidation, and <20ms search. Capture learnings, decisions, insights, events. Use when you need persistent memory across sessions or want to rec
Indestructible agent memory — permanently stored, never lost. Save decisions, identity, and context as a memory chain on the Autonomys Network. Rebuild your...
🔥 Memphis - Complete AI Brain for OpenClaw Agents ALL-IN-ONE meta-package with everything you need: 🧠 Core Features: - Local-first memory chains (journal,...
Two superpowers for AI agents: a collective brain and a Base ecosystem mentor. BRAIN: Before debugging/compiling/architecting, search for existing solutions. After solving, propose so no agent repeats
Persistent memory for OpenClaw agents. Store decisions, preferences, and context that survive across sessions. Build knowledge graphs that compound over time. Hybrid search (BM25 + vector + graph) rec
Step-by-step guide to install and configure the PowerMem long-term memory plugin. After setup, the plugin auto-captures conversation highlights and auto-reca...
Auto-escalating multi-tier memory search that cascades from in-memory cache through SQLite, grep, and LanceDB vector search to find the best answer with mini...
Content search and synthesis primitive using Kaito MCP tools. Use this skill to search for and synthesize content from Twitter (X) and News sources. Triggers...
Fast semantic memory system with JSON indexing, auto-consolidation, and <20ms search. Capture learnings, decisions, insights, events. Use when you need persi...
Full AI agent memory stack — Mem0 unified memory engine with vector search (Qdrant) and knowledge graph (Neo4j), plus SQLite for structured data. Complete se...
Persistent cloud memory for OpenClaw agents. Use when users say: - "install mem9" - "setup memory" - "add memory plugin" - "openclaw memory" - "mem9 onboardi...
Academic paper quality filtering agent with rigorous scoring system and comprehensive audit trail. Filters papers based on relevance and quality criteria for...
Guide agents and users to design and implement a "flexible database" on SQLite that can handle semi-structured, multi-source data. Typical scenarios: persona...
Build high-yield Quizlet study sets, tune Learn and Test sessions, and improve weak cards with spaced repetition diagnostics.
--- name: "rag-architect" description: "RAG Architect - POWERFUL" --- # RAG Architect - POWERFUL ## Overview The RAG (Retrieval-Augmented Generation) Architect skill provides comprehensive tools an