Loading...
Loading...
Found 85 Skills
Persistent key-value memory storage for agents. Store and recall information across conversations and sessions. Use when you need the agent to remember facts, preferences, or data between interactions.
Nightly memory consolidation — prunes stale entries, merges duplicates, resolves contradictions, rebuilds MEMORY.md index. Use when memory files have accumulated over many sessions and need cleanup. Do NOT use for storing new decisions (use remember) or searching memory (use memory).
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'.
Hybrid memory strategy combining OpenClaw's built-in QMD vector memory with Graphiti temporal knowledge graph. Use for all memory recall requests.
Persistent shared memory for AI agents backed by PostgreSQL (fts + pg_trgm, optional pgvector). Includes compaction logging and maintenance scripts.
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.
This skill installs and configures the **Tablestore Mem0** plugin for OpenClaw. Tablestore Mem0 uses Alibaba Cloud Tablestore as the vector store backend for mem0, providing persistent long-term memory for AI agents. Use this skill when the user wants OpenClaw to persist or manage long-term memory using Alibaba Cloud Tablestore as the backend. Triggers: "set up tablestore memory", "install tablestore mem0 plugin", "configure long-term memory with tablestore", "remember this".
Scaffold or audit the memex (vault + AGENTS.md + spec templates + bundled skills) in any repo — an externalized, navigable project memory for agents (Claude Code, Codex, Cursor, OpenCode, etc.). Agent-agnostic. Idempotent — safe to run repeatedly. Use when the user wants to set up, verify, or fix the memex in a project.
Use when conversation context is too long, hitting token limits, or responses are degrading. Compresses history while preserving critical information using anchored summarization and probe-based validation.
Layer agentic capabilities onto a full-stack Eve app — agents, teams, multi-model inference, memory, events, chat, and coordination. Use when designing an app where agents are primary actors, not afterthoughts.
Maintain a structured ledger of decisions, discovered bugs and fixes, user preferences, constraints, current status, and failed approaches throughout multi-step agentic tasks. Auto-update after every significant step. Triggers on "where were we", "continue", "summarize status", "remember", or when a new agent instance takes over a task.