OpenAEON: Open-source implementation of the AEON Protocol for advanced AI cognitive observability, featuring real-time

by openaeon · Codex Skill · ★ 90

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How to install OpenAEON

git clone https://github.com/openaeon/OpenAEON.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 58/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

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.

agentagentsaiassistantcrustaceanopenaeonopenclawopenclaw-pluginpersonal

Quick Facts

Stars90
Forks22
LanguageTypeScript
CategoryCodex Skill
LicenseMIT
Quality Score58/100
Open Issues6
Last Updated2026-07-30
Created2026-03-09
Platformsnode
Est. Tokens~17743k

About OpenAEON

🌌 OpenAEON English | 中文 AEON PROPHET — A Species-Level Evolution of the Logic Layer “Not a framework upgrade. A new form of intelligence architecture.” Watch Demonstration 🖼 UI Screenshots (Dark Mode, UI) Chat (, UI) Sandbox (, UI) AEON (, UI) 🧠 FCA Core (Fractal Cognitive Adapter) OpenAEON is powered by the FCA Core, a multi-layer cognitive archite

Compatible Skills

These tools work well together with OpenAEON for enhanced workflows:

  • Lucid — semantic(0.27)+complementary+same_lang+similar_pop+shared_platform (60%)
  • openclaw-nerve — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (53%)

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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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