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Found 104 Skills
Design short-term, long-term, and graph-based memory architectures
Supermemory is a state-of-the-art memory and context infrastructure for AI agents. Use this skill when building applications that need persistent memory, user personalization, long-term context retention, or semantic search across knowledge bases. It provides Memory API for learned user context, User Profiles for static/dynamic facts, and RAG for semantic search. Perfect for chatbots, assistants, and knowledge-intensive applications.
Design and configure AI agents for Polpo — models, tools, identity, memory, vault, and system prompts. Use when the user wants to create an agent, configure agent capabilities, set up agent memory, manage agent credentials (vault), choose models, assign tools, or architect multi-agent systems. Triggers on "polpo agent", "configure agent", "agent design", "agent tools", "agent memory", "agent vault", "system prompt", "agent identity".
Explicitly save an insight, decision, or learning to agentmemory's long-term storage. Use when the user says "remember this", "save this", or wants to preserve knowledge for future sessions.
Delete specific observations or sessions from agentmemory. Use when user says "forget this", "delete memory", or wants to remove specific data for privacy.
Resume the most recent agent session for the current working directory. Use when the user says "where were we", "resume", "handoff", "pick up where I left off", or starts a session with no fresh context.
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.
AI Agent long-term memory system with cross-session, cross-project persistence. Triggers: - /remember - Store memories - /recall - Search memories - /forget - Delete/archive memories - /memory-status - Check status - When needing to persist important conversation insights - When sharing user preferences across projects
Configure Lakebase for agent memory storage. Use when: (1) Adding memory capabilities to the agent, (2) 'Failed to connect to Lakebase' errors, (3) Permission errors on checkpoint/store tables, (4) User says 'lakebase', 'memory setup', or 'add memory'.
Manage git-backed memory repos. Load this skill when working with git-backed agent memory, setting up remote memory repos, resolving sync conflicts, or managing memory via git workflows.
Hybrid memory strategy combining OpenClaw's built-in QMD vector memory with Graphiti temporal knowledge graph. Use for all memory recall requests.
Agent skill for v3-memory-specialist - invoke with $agent-v3-memory-specialist