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 ningzimu · Claude Skill · ★ 56
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is codex-gpt-image safe to install? View the security audit →
Codex GPT Image Skill 一个面向 OpenClaw / Claude Code / Codex / Hermes Agent 的 生图 skill：通过 Codex OAuth / ChatGPT 登录态 调用 ，不需要 。 它读取本机 ，请求 ，并显式调用 Responses 工具，让 agent 复用已有 Codex / ChatGPT 订阅权限生成图片。 适合谁用 想在 OpenClaw / Claude Code / Codex / Hermes Agent 里直接用 生图 已经有 Codex / ChatGPT OAuth 登录态，不想再配置 OpenAI API key 想把同一套 GPT Image skill 复用到多个支持 的 agent 需要文本生图、参考图编辑、2K/4K 输出或透明背景请求 特点 OpenClaw skill / Claude Code skill / Codex skill / Hermes Agent skill Codex OAuth：读取 ，不要求 OpenAI API key 默认使用 ，支持 、、、 质量参数 支持文本生图和多参考图编辑 支持 2K/4K 合法尺寸，例如 、 支持透明背景请求自动使用 纯 Python 标准库脚本，便于在任意 agent 环境里调用 目录结构 安装 推荐使用 CLI 一次安装到当前 agent 的全局 skills 目录： 这个仓库目前只包含 一个 skill。安装完成后
| Stars | 56 |
| Forks | 2 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 64.8740634882873/100 |
| Last Updated | 2026-09-10 |
| Created | 2026-05-11 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~5k |
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codex-gpt-image is OpenClaw/Claude Code SKILL.md for gpt-image-2 via Codex OAuth, no OPENAI_API_KEY required. It is categorized as a Claude Skill with 56 GitHub stars.
codex-gpt-image is primarily written in Python. It covers topics such as agent-skills, claude-code, claude-code-skill.
You can find installation instructions and usage details in the codex-gpt-image GitHub repository at github.com/ningzimu/codex-gpt-image. The project has 56 stars and 2 forks, indicating an active community.
codex-gpt-image is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to codex-gpt-image on Agent Skills Hub include mcp-image, skills, agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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: