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by leeguooooo · Codex Skill · ★ 353
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🔒 Is chatgpt-imagegen safe to install? View the security audit →
chatgpt-imagegen English | 中文 Generate images using your ChatGPT subscription — no needed. A tiny, zero-dependency Python CLI (and AI-agent skill) — one file, stdlib only — that generates images with your ChatGPT account, on the command line and for any AI agent. ✨ Works on a free ChatGPT account too. The default backend just drives the normal ChatGPT web chat, where even free-tier users get image generation — so no paid plan, no API key, and no Codex required (subject to the free tier's daily image limit). Paid plans simply get higher limits. Why this exists OpenAI offers image generation in two completely separate ways: The subscription path is invisible to people who don't use the Codex CLI. It runs on ChatGPT's internal endpoint as a Responses-API tool, authenticated by the OAuth toke
| Stars | 353 |
| Forks | 40 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 70.4668094219043/100 |
| Last Updated | 2026-09-11 |
| Created | 2026-05-18 |
| Platforms | claude-code, cli, codex, python |
| Est. Tokens | ~17k |
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chatgpt-imagegen is Use your ChatGPT subscription to generate images from the command line — no OPENAI_API_KEY, no gateway, no daemon. Zero-dep Python CLI + AI-agent skill.. It is categorized as a Codex Skill with 353 GitHub stars.
chatgpt-imagegen is primarily written in Python. It covers topics such as agent-skill, chatgpt, chatgpt-plus.
You can find installation instructions and usage details in the chatgpt-imagegen GitHub repository at github.com/leeguooooo/chatgpt-imagegen. The project has 353 stars and 40 forks, indicating an active community.
chatgpt-imagegen is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to chatgpt-imagegen on Agent Skills Hub include gpt_image_2_skill, ilab-gpt-conjure, dsh-codex-subscription. 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.
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