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 Wangnov · Codex Skill · ★ 137
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is gpt-image-2-skill safe to install? View the security audit →
gpt-image-2-skill Language: 中文 | English 一个 Rust core 跑四种入口的 GPT Image 2 工具链。CLI、桌面 App、自托管 Docker Web、可安装 Skill 共用同一份 provider 适配层、透明 PNG 流水线、配置与本地历史,统一以 agent-first 的 JSON stdout + JSONL stderr 协议输出结果。 目录 架构 项目定位 快速开始 运行时矩阵 Provider 矩阵 核心能力 图像生成与编辑 透明 PNG 流水线 Agent 协议 配置与密钥 [桌面 App](#桌面-app
| Stars | 137 |
| Forks | 14 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 64.5996866588219/100 |
| Open Issues | 20 |
| Last Updated | 2026-09-13 |
| Created | 2026-04-22 |
| Platforms | browser, cli, codex, node |
| Est. Tokens | ~26k |
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gpt-image-2-skill is GPT Image 2 Skill / CLI / Web / Desktop. It is categorized as a Codex Skill with 137 GitHub stars.
gpt-image-2-skill is primarily written in TypeScript. It covers topics such as chatgpt, codex, gpt-image-2.
You can find installation instructions and usage details in the gpt-image-2-skill GitHub repository at github.com/Wangnov/gpt-image-2-skill. The project has 137 stars and 14 forks, indicating an active community.
gpt-image-2-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to gpt-image-2-skill on Agent Skills Hub include ilab-gpt-conjure, desktop, chatgpt-imagegen. 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: