everything-openai-codex — security grade SAFE, quality 65/100

Security audit verdict: SAFE · quality 65/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by mturac · Codex Skill · ★ 87

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

🔒 Is everything-openai-codex safe to install? View the security audit →

About everything-openai-codex

Language: English ไทย Everything OpenAI Codex ![Markdown](https://im

agent-harnessagent-skillsai-agentsautomationcli-toolscodexcodex-clicodex-pluginscoding-assistantcopilot

Quick Facts

Stars87
Forks4
LanguageJavaScript
CategoryCodex Skill
LicenseMIT
Quality Score64.8100434599302/100
Open Issues8
Last Updated2026-07-27
Created2026-05-18
Platformscli, codex, gemini, node
Est. Tokens~25k

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Frequently Asked Questions

What is everything-openai-codex?

everything-openai-codex is EOC: open-source operating system for OpenAI Codex workflows with agents, skills, hooks, rules, memory, safety gates, and cross-harness adapters.. It is categorized as a Codex Skill with 87 GitHub stars.

What programming language is everything-openai-codex written in?

everything-openai-codex is primarily written in JavaScript. It covers topics such as agent-harness, agent-skills, ai-agents.

How do I install or use everything-openai-codex?

You can find installation instructions and usage details in the everything-openai-codex GitHub repository at github.com/mturac/everything-openai-codex. The project has 87 stars and 4 forks, indicating an active community.

What license does everything-openai-codex use?

everything-openai-codex is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to everything-openai-codex?

The top alternatives to everything-openai-codex on Agent Skills Hub include agent-skills, untether, awesome-ai-agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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:

View on GitHub → Browse Codex Skill tools