Deus: A token-efficient open-source AI assistant that remembers, adapts, and improves

by sliamh11 · Agent Tool · ★ 51

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install Deus

git clone https://github.com/sliamh11/Deus.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: CAUTION · quality 71/100

Flagged: opens a tunnel service. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-assistantai-memoryclaude-codecontainer-isolationpersistent-memoryself-improving-aisemantic-memorysemantic-search

Quick Facts

Stars51
Forks6
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score71/100
Open Issues60
Last Updated2026-10-30
Created2026-03-21
Platformsclaude-code, python
Est. Tokens~17k

About Deus

A personal AI that understands you - not just recalls things you've said. It learns what you care about, how you think, and what you'll actually find useful. The longer you use it, the more it feels like it gets you. Everything runs on your computer. Your data stays yours.

Deus alternative? Top 6 similar tools

Looking for a Deus alternative? If you're comparing Deus with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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  • openclaw-config by TechNickAI · ⭐ 75

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  • yantrikdb by yantrikos · ⭐ 72

    Cognitive memory engine for AI agents — temporal decay, contradiction detection, autonomous consolidation, kno

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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