jzOcb

jzOcb / openclaw-memory-management

Public

AI Agent 记忆管理系统：P0/P1/P2 优先级 + 自动归档，Token 降 78%

24
6
100% credibility
Found Feb 18, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Python
AI Summary

A tool to organize and automatically archive memories for OpenClaw AI agents using priority levels to minimize token usage and keep performance high.

How It Works

1
🤔 Notice the Issue

You realize your AI assistant is getting slower and using more space as it stores more memories over time.

2
🔍 Discover the Helper

You find this simple memory organizer designed to keep your AI's memories tidy and efficient.

3
📋 Set Up Memory Notebook

You grab ready-made templates and place them in your AI workspace to start sorting memories into permanent, project, and temporary sections.

4
⏰ Schedule Auto-Cleanup

You set a daily routine so old temporary notes get safely archived without you lifting a finger.

5
🧹 Test the Cleanup

You preview what gets moved and run it once to watch your memory file shrink while keeping the important stuff.

6
🚀 Add Smart Recall

You connect optional helpers so your AI can still search old lessons without loading everything.

🎉 AI Stays Sharp

Now your AI thinks faster, uses way less space, and stays smart by focusing on what matters most.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 16 to 24 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is openclaw-memory-management?

This Python tool manages memory for OpenClaw AI agents, sorting notes into P0 (permanent core identity), P1 (90-day active projects), and P2 (30-day temporary) priorities to prevent bloat. It auto-archives expired entries via a cron job, keeping hot memory under 200 lines while dumping the rest to searchable archives and structured lessons for semantic recall. Users get a 78% token drop, turning bloated agent github repos into lean machines without manual cleanup.

Why is it gaining traction?

Unlike generic agent memory hacks in agent github copilot reddit threads or agent github openai setups, it delivers instant 78% token wins with dead-simple CLI flags for dry runs, stats, and archiving—pair it with agent github action for hands-off maintenance. The priority system beats full-scan recalls in agent github code, and integrations for OpenClaw skills or Claude projects make it plug-and-play for agent github microsoft or google github agent workflows.

Who should use this?

OpenClaw builders drowning in token limits from endless logs, or agent devs on agent github copilot intellij juggling long-running bots with scattered rules. Ideal for solo agent github repo maintainers needing auto-pruning without losing key lessons, especially in production setups with daily cron needs.

Verdict

Grab it if you're deep in OpenClaw—templates and cron setup yield quick wins despite 16 stars and 1.0% credibility signaling early-stage code. Solid docs for a niche tool, but test thoroughly before trusting with critical agent memory management.

(178 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.