awesome-gpt-image-2 is a collection of prompts and reusable templates for generating images with GPT-Image-2. It helps people study, adapt, and apply image-generation prompts across different styles and scenarios.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add freestylefly/awesome-gpt-image-2 --skill gpt-image-2-style-librarygit clone --depth 1 https://github.com/freestylefly/awesome-gpt-image-2Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/freestylefly/awesome-gpt-image-2/gpt-image-2-style-library)<a href="https://agentmods.dev/skills/freestylefly/awesome-gpt-image-2/gpt-image-2-style-library"><img src="https://agentmods.dev/badge/skills/freestylefly/awesome-gpt-image-2/gpt-image-2-style-library/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/freestylefly/awesome-gpt-image-2/gpt-image-2-style-library"><img src="https://agentmods.dev/badge/skills/freestylefly/awesome-gpt-image-2/gpt-image-2-style-library.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.00522 |
| Opus 5.5 | $0.00029 | $0.00209 |
| Sonnet 5.5 | $0.00014 | $0.00104 |
| Haiku 4.5 | $0.00007 | $0.00052 |
Grade A, and why
gpt-image-2-style-library scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GPT-Image2 Style Library
Use this skill to turn a user's image-generation intent into a production-ready GPT-Image2 prompt using the awesome-gpt-image-2 style library.
Example Output
Example request: 用 gpt-image-2-style-library 技能生成城市生命系统图谱
Reference
- Read
references/style-library.mdbefore choosing a template or style. - The reference is generated from
data/style-library.jsonin the repository. - Prefer the reference over memory when template names, categories, covers, or style tags matter.
Workflow
- Detect the user's language and answer in that language.
- Identify the user's target output: product, poster, UI, infographic, brand, photo, illustration, character, scene, history, document, or special task.
- Match the request in this order: template category, visual style tag, scene tag, then nearest example cases.
- If one template is clearly strongest, use it directly. If several are plausible, present 2-3 options with short reasons and ask the user to choose.
- Build the final prompt with these blocks:
- subject and task
- composition and layout
- visual style and materials
- text and label requirements
- aspect ratio and output format
- constraints and negative details
- Include the selected template name and any useful example case IDs.
Output Defaults
- Provide a copyable prompt first.
- Keep constraints concrete: exact text, aspect ratio, readable labels, layout hierarchy, and avoided artifacts.
- For Chinese requests, write the final prompt in Chinese unless the user asks for English.
- For English requests, write the final prompt in English unless the user asks for Chinese.
- When the user asks for multiple concepts, reuse one template and vary subject, composition, palette, and scene.
Maintenance
When the source repository changes, run:
npm run generate:style-skill
To install the skill into the local Codex skill folder, run:
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 58 lines · 72 tokens per session scan A 98519a3bfd28
gpt-image-2-style-library is a skill published in the GitHub repository freestylefly/awesome-gpt-image-2 (35,122 stars, last pushed 13d ago), licensed MIT. It adds 72 tokens to every session and 522 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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