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 wuyoscar · Codex Skill · ★ 5.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is GPT-Image2-Skill safe to install? View the security audit →
GPT Image 2 Prompt Gallery + Agentic Skill + CLI OpenAI GPT Image 2 prompt gallery, image prompt library, agentic skill, and CLI — curated, copy-paste prompts and runnable examples for skill-capable agents. English · 中文 <img src="https://img.shields.io/static/v1?label=oosmetrics&message=Top%201
| Stars | 5,524 |
| Forks | 467 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 65.6135764242815/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-09 |
| Created | 2026-04-22 |
| Platforms | claude-code, cli, codex, python |
| Est. Tokens | ~25k |
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GPT-Image2-Skill is GPT Image 2/2.5 prompt gallery, image prompt library, agentic skill, and CLI for OpenAI image generation/editing. It is categorized as a Codex Skill with 5.5k GitHub stars.
GPT-Image2-Skill is primarily written in Python. It covers topics such as agent-skills, ai-image-prompts, claude-code-skill.
You can find installation instructions and usage details in the GPT-Image2-Skill GitHub repository at github.com/wuyoscar/GPT-Image2-Skill. The project has 5.5k stars and 467 forks, indicating an active community.
GPT-Image2-Skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to GPT-Image2-Skill on Agent Skills Hub include awesome-gpt-image-2, Generative-Media-Skills, nano-banana-pro-prompts-recommend-skill. 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: