shared-memory

Read and write a shared memory log for cross-device bot continuity.

Updated Mar 7, 2026
One-click install
npx skills add https://github.com/bibo1243/claw_memory --skill shared-memory-bibo1243
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: shared-memory
Source: https://github.com/bibo1243/claw_memory/tree/main/gaa_all/.agent/skills/shared-memory
Command: npx skills add https://github.com/bibo1243/claw_memory --skill shared-memory-bibo1243

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Two bots (GaaClaw and gaa1243) share a memory log to read before a conversation and write after, enabling memory synchronization across local and cloud deployments.

Core Features & Use Cases

  • Read memory: fetch the latest content from gaa_all/對話.md to understand what the other bot said.
  • Write memory: append the current dialogue to gaa_all/對話.md with a timestamp and bot name to maintain continuity.
  • Use Case: maintain cross-device conversation context between a MacBook-based bot and a cloud-based bot.

Quick Start

Read the latest shared memory and append your messages to gaa_all/對話.md.

Frequently Asked Questions about shared-memory

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

FAQPage Schema
How do I sync memory between two bots across different devices?

You can sync memory between two bots by using a Python script to read and append dialogue to a shared memory log located at gaa_all/對話.md, ensuring cross-device context continuity.

What is shared memory synchronization for chat workflows?

Shared memory synchronization for chat workflows is the process of persisting conversational context between separate bot sessions by writing current dialogue to and reading past dialogue from a shared log file.

Do I need external libraries to set up Python-based memory synchronization?

No, you do not need external libraries for this Python-based memory synchronization setup; it requires only the Python standard library to read and write to the local shared log file.

Can I maintain cross-device conversation context using a local file?

Yes, you can maintain cross-device conversation context using a local file by setting up a simple Python script that appends messages with a timestamp and bot name to a shared memory log.

What are the limitations of using a shared log file for bot memory sync?

A limitation of using a shared log file for bot memory sync is that it relies on basic file read and write operations, which may lack concurrent transaction safety for simultaneous bot writings.