LeoYeAI

LeoYeAI / openclaw-auto-dream

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Automatic memory consolidation for OpenClaw agents — like sleep for your AI. Powered by MyClaw.ai

myclaw.ai ai-agent auto-dream llm memory memory-management
47
0
69% credibility
Found Mar 30, 2026 at 48 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
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AI Summary

OpenClaw Auto-Dream is a skill for AI agents that simulates human-like memory consolidation through automated nightly cycles, organizing knowledge into layers, scoring importance, generating insights, and providing visual health dashboards.

How It Works

1
🔍 Discover your smart AI companion

You hear about MyClaw, a helpful AI that runs on its own server and never forgets important things with a special dreaming skill called Auto-Dream.

2
💬 Tell your AI to add the dreaming skill

Simply chat with your AI assistant and say 'Install Auto-Dream' – it handles everything automatically like a helpful friend.

3
⚙️ Set your preferences

Your AI asks how often you want updates and notifications, then gets everything ready in moments.

4
🌙 Watch the magic of the first dream

Overnight, your AI 'dreams' by sorting old notes into smart memory layers, scoring what's important, and waking up wiser.

5
📱 Get a dream report in your chat

Wake up to a friendly summary in your chat showing new insights, health check, and smart suggestions from your AI's dream.

6
View your memory dashboard
🔄
Move memories to a new setup

Easily carry your AI's memories to another place if you switch servers.

✅
Keep enjoying daily dreams

Let it run automatically every night for ongoing smarter conversations.

🧠✨ Your AI becomes a true partner

Now your assistant remembers everything perfectly, spots patterns you miss, and feels like a brilliant teammate who grows with you.

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Star Growth

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AI-Generated Review

What is openclaw-auto-dream?

OpenClaw Auto-Dream adds automatic memory management to OpenClaw AI agents, mimicking human sleep cycles to consolidate logs into structured layers like episodic facts and workflows. It scans daily entries, scores importance with recency and references, applies gradual forgetting via archiving, and generates HTML health dashboards plus push notifications—all via cron jobs on your server. Developers get persistent AI memory without manual cleanup, turning raw logs into queryable knowledge for agents handling long-term tasks.

Why is it gaining traction?

Unlike flat-file memory plugins or basic key-value stores, it layers memories cognitively (working, episodic, long-term), builds knowledge graphs for connections, and tracks health across five metrics with interactive visualizations. Users notice smarter agents that learn from history, detect patterns like stalled threads, and migrate memories across servers seamlessly. The zero-dependency setup via ClawHub or agent commands hooks devs tired of amnesia in persistent AI agents.

Who should use this?

MyClaw.ai users running 24/7 OpenClaw agents for project management, workflow automation, or code assistance, especially those dealing with accumulating logs from automatic GitHub commits, pushes, releases, or dependency submissions. Ideal for solo devs or teams needing automatic memory cleaners to maintain context over weeks without constant retraining.

Verdict

Grab it if you're in the OpenClaw ecosystem—solid docs in eight languages and non-destructive upgrades make it easy to try, despite 47 stars signaling early maturity. Low 0.7% credibility score reflects niche appeal, but it delivers real automatic memory management value for agents today.

(198 words)

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