triple-memory

Name: triple-memory
Availability: InStock
Author: xianmingyao

Integrate LanceDB auto-recall, Git-Notes memory, and file-based workspace search for persistent context.

1|1|Updated Mar 18, 2026

Search Tags:#memory #lancedb #multi-backend #persistent-context #git-notes #workspace-search

Ready to run

npx skills add https://github.com/xianmingyao/openclaw-CaySon --skill triple-memory-xianmingyao

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: triple-memory
Source: https://github.com/xianmingyao/openclaw-CaySon/tree/main/skills/triple-memory
Command: npx skills add https://github.com/xianmingyao/openclaw-CaySon --skill triple-memory-xianmingyao

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Triple-memory unifies multiple memory backends to preserve context across AI sessions, enabling persistent context and coordinated decision memory.

Core Features & Use Cases

LanceDB auto-recall and auto-capture for conversation memory
Git-Notes memory for structured decisions, entity extraction, and branch awareness
File Search (workspace) to index and recall workspace documents
Use cases include long-term context maintenance, cross-session continuity, and multi-backend memory orchestration

Quick Start

Initialize the triple memory workflow by starting LanceDB auto-recall, synchronizing Git-Notes memory, and enabling the file search in your workspace.

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 AI context across multiple sessions?▼

To maintain persistent AI context across sessions, you can use a multi-backend memory system that unifies vector database auto-recall, Git-Notes, and workspace file search to preserve decisions and conversations.

What is the best way to coordinate long-term memory for AI agents?▼

Coordinating long-term memory for AI agents is best achieved through a unified memory system that orchestrates multiple backends, enabling cross-session continuity and preserving task context.

How does LanceDB auto-recall work for conversation memory?▼

LanceDB auto-recall works by automatically capturing conversation context into a vector database and retrieving relevant memories during AI sessions without manual intervention.

Can I use Git-Notes to store structured decisions for AI workflows?▼

Yes, you can use Git-Notes to store structured decisions for AI workflows, extracting entities and maintaining branch awareness to preserve context within your repository's history.

Do I need a separate script to index workspace files for AI context?▼

You need a file-search script to index workspace files for AI context, allowing the memory system to recall local documents and integrate them into the persistent context workflow.

What are the limitations of multi-backend memory orchestration for AI?▼

Limitations of multi-backend memory orchestration include the dependency on coordinating distinct systems like a vector database, Git-Notes, and file search, which requires initial setup to synchronize correctly.