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triple-memory

Integrate LanceDB, Git-Notes, and file search for persistent agent memory.

Updated Feb 3, 2026
Search Tags:#context#agent#memory#persistence#lancedb#git-notes
One-click install
npx skills add https://github.com/sky770825/openclaw-console-hub --skill triple-memory-sky770825
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: triple-memory
Source: https://github.com/sky770825/openclaw-console-hub/tree/main/skills/triple-memory
Command: npx skills add https://github.com/sky770825/openclaw-console-hub --skill triple-memory-sky770825

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of maintaining consistent and comprehensive context for AI agents by integrating multiple memory systems, ensuring that crucial information is never lost and is readily accessible across different operational contexts.

Core Features & Use Cases

  • Multi-Backend Memory: Combines LanceDB for auto-recall/capture, Git-Notes for structured, branch-aware memory, and file search for workspace context.
  • Persistent Context: Ensures agent memory persists across sessions and is aware of project-specific nuances via Git branches.
  • Use Case: An AI assistant working on a software project can use this system to recall past decisions, track architectural choices specific to a feature branch (Git-Notes), and quickly search through project documentation or notes (File Search).

Quick Start

Set up the LanceDB plugin and install the Git-Notes memory skill.

Frequently Asked Questions about triple-memory

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I maintain persistent agent memory across different conversation sessions?▼

Persistent agent memory is maintained by integrating LanceDB for automatic conversation recall and capture alongside Git-Notes for structured entity extraction. This multi-layered architecture ensures context is never lost across operational sessions.

What is the best way to track AI agent decisions specific to a Git feature branch?▼

Tracking AI agent decisions per Git feature branch is handled by the Git-Notes memory system, which provides structured, branch-aware memory logging. It ensures project-specific context and architectural choices are isolated accurately.

How does LanceDB work with AI agents for automatic context recall?▼

LanceDB works as a memory backend that automatically captures conversation context and recalls relevant information when the AI agent operates. It provides persistent recall without manual data entry.

Do I need to install separate plugins to enable workspace document retrieval and conversation memory?▼

You need to set up the LanceDB plugin and install the Git-Notes memory skill to enable both workspace document retrieval via file search and persistent conversation memory. This combination provides multi-backend memory.

Can I use a multi-backend memory architecture to search project documentation and log decisions simultaneously?▼

A multi-backend memory architecture combines file search for workspace document retrieval with Git-Notes for branch-aware decision logging. This allows an AI assistant to search documentation while simultaneously tracking architectural choices.

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