Recall past conversations and user preferences with searchable long‑term memory. Organize work into spaces and quickly load rich project context. Act across connected services like GitHub, Linear, and
High-precision memory with 100% recall accuracy for long contexts.
Persistent semantic memory for AI agents. SQLite-backed, local-first, zero config. Semantic search via Ollama embeddings (nomic-embed-text) with keyword fallback. remember, recall, history, forget, an
Persistent memory plugin for OpenClaw agents. Hybrid SQLite FTS5 keyword + Ollama vector semantic search with auto-capture, auto-recall, stuck-detection, and...
Search, summarize, and extract insights from your Limitless AI pendant life logs. Supports keyword and semantic search, date range queries, memory recall, an...
Long-term structured memory with knowledge graph, entity tracking, temporal reasoning, and cross-session recall. Powered by the Cortex API.
Structure study sessions, manage materials, and prepare for exams with active recall techniques.
The best way to access Telegram message history. Use this skill whenever the user asks about their Telegram messages, chats, DMs, or groups — search, summarize, extract action items, recall conversa
Provides a highly visual and interactive dashboard for OpenClaw users to easily understand and recall the functionalities of installed skills, featuring a vi...
Dead code detection, security scanning, and code quality analysis for Python, TypeScript, and Go. 98% recall with fewer false positives than Vulture. Includes AI-powered remediation.
Provides OpenClaw agents with local, scene-aware, persistent structured memory for task deduplication and long-term workflow recall.
Memory-as-a-Service for AI agents. Store and recall memories with semantic vector search. 100 free calls per wallet, then x402 micropayments. Your wallet add...
Recall memories from MemOS Cloud before responding. Use this skill when you need context about user's previous conversations, preferences, or decisions.
Local semantic memory with Qdrant and Transformers.js. Store, search, and recall conversation context using vector embeddings (fully local, no API keys).
Structured AI agent memory with categorized storage, MD5 duplicate detection, consolidation, keyword recall, and export in Markdown or JSON formats.
Human-like memory layer for AI agents with semantic, episodic, and procedural memory. Claude Code hooks (auto-save, auto-recall, cognitive profile). 29 MCP tools, knowledge graph, smart triggers, mult
Session-first memory curator for OpenClaw. Keeps RAM clean, recall precise, and durable knowledge safe.
Structure and track learning with spaced repetition and active recall across any domain.
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
7-layer recursive agent memory with context branching, holographic recall, dream consolidation, and on-chain persistence. MCP-native with 10 tools for persistent agent cognition.
Write session summaries to daily memory files and search session history so OpenClaw can recall and cite past conversations.
Install, update, and monitor E.x.O. tools like jasper-recall and hopeIDS, manage OpenClaw plugins, and perform health checks with a single command.
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...
Hybrid memory strategy combining OpenClaw's built-in vector memory with Graphiti temporal knowledge graph. Use when you need to recall past context, answer temporal questions ("when did X happen?"), o