Audit, clean, and optimize Clawdbot's vector memory (LanceDB). Use when memory is bloated with junk, token usage is high from irrelevant auto-recalls, or setting up memory maintenance automation.
Persistent memory system for AI agents to remember facts, learn from experiences, recall memories, and track entities across sessions.
--- name: infinite-memory version: 1.0.0 description: High-precision memory with 100% recall accuracy for long contexts. emoji: 🦞 metadata: clawdbot: requires: bins: -
--- name: ctxly version: 1.0.0 description: Cloud memory for AI agents. Store, search, and recall context across sessions. homepage: https://ctxly.app metadata: {"emoji": "🧠", "category": "memory",
Recall memories from MemOS Cloud before responding. Use this skill when you need context about user's previous conversations, preferences, or decisions.
Persistent memory system for AI agents — daily logs, long-term memory, identity files, and heartbeat-driven recall. Solves context amnesia across sessions.
Manage and update a layered memory system using daily files as source, indexing by domain/module/entity, extracting critical facts, and maintaining recall ef...
Adds intelligent long-term memory to agents for auto-capturing, recalling, and managing user facts and preferences across sessions.
Resume multi-session projects with full context retention. Use when returning to previous work, needing conversation history, recalling past decisions, or br...
Track and recall your daily activities including git commits, web browsing, shell commands, and VS Code edits. Use this skill whenever the user asks about th...
Local semantic memory with Qdrant and Transformers.js. Store, search, and recall conversation context using vector embeddings (fully local, no API keys).
Search and browse past conversation history across all sessions. Use when recalling prior work, finding old discussions, resuming dropped threads, or when th...
Structured memory system for AI agents. Use when the user wants to store, recall, or search memories, manage session lifecycle (wake/sleep/checkpoint), sync...
Persistent semantic memory for AI agents — local, fast, free. Use when agent needs to recall past decisions, store new facts/preferences, search conversation history, or maintain context across sessio
Long-term memory via ChromaDB with local Ollama embeddings. Auto-recall injects relevant context every turn. No cloud APIs required — fully self-hosted.
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
Provides OpenClaw agents with local, scene-aware, persistent structured memory for task deduplication and long-term workflow recall.
MongoDB-backed long-term semantic memory for recalling, storing, searching, and managing facts, decisions, and user preferences across sessions.
Provides persistent, searchable AI agent memory with real-time capture, vector search, and nightly LLM curation for long-term recall on local hardware.
Cloud memory for AI agents. Store, search, and recall context across sessions.
Persistent memory for AI agents to store facts, learn from actions, recall information, and track entities across sessions.