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 modu-ai/moai-cowork --skill media-gpt-image-2-promptgit clone --depth 1 https://github.com/modu-ai/moai-coworkWrote 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/modu-ai/moai-cowork/media-gpt-image-2-prompt)<a href="https://agentmods.dev/skills/modu-ai/moai-cowork/media-gpt-image-2-prompt"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-cowork/media-gpt-image-2-prompt/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/modu-ai/moai-cowork/media-gpt-image-2-prompt"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-cowork/media-gpt-image-2-prompt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00278 | $0.03792 |
| Opus 5 | $0.00139 | $0.01896 |
| Sonnet 5 | $0.00056 | $0.00758 |
| Haiku 4.5 | $0.00028 | $0.00379 |
Grade A, and why
media-gpt-image-2-prompt 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 8d 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 — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GPT-image-2 Prompt Builder — 6-Block 구조 + 3-모델 동시 출력
moai-coworker | 이미지 프롬프트 빌더 (텍스트 산출 전용)
개요
OpenAI GPT-image-2 모델은 자연어를 art-director 어조로 이해하는 reasoning-driven 이미지 모델입니다. 본 스킬은 사용자 한 줄 요청을 OpenAI Cookbook이 권장하는 6-Block 구조(Subject → Action → Scene → Composition → Lighting → Style & Text Constraints)로 풀어 써서 ChatGPT 또는 OpenAI API에 그대로 복붙할 수 있는 프롬프트를 출력합니다.
특히 본 스킬은:
- 3개 모델 동시 출력: GPT-image-2 메인 프롬프트와 함께 동일한 의도를 Gemini 3 Pro Image(5-component)와 Midjourney v8.1(키워드+
--파라미터) 어조로도 변환해 한 화면에 제공합니다. - 프리셋 + 미세조정: 4개 프리셋(제품샷·인물·일러스트·풍경)으로 학습 곡선을 낮추고, 프리셋별 3-4개 미세조정 질문으로 디테일을 확보합니다.
- 텍스트 verbatim 보장: 이미지에 들어갈 글자는 따옴표·ALL CAPS·verbatim 지시로 GPT-image-2의 95%+ 텍스트 렌더링 정확도를 활용합니다.
본 스킬은 프롬프트 텍스트만 산출합니다. 사용자가 원하는 도구(ChatGPT 웹, Sora, OpenAI Playground 등)에서 직접 복붙해 사용하거나, Higgsfield MCP(Soul) 직접 호출로 이미지를 생성합니다.
트리거 키워드
GPT 이미지 프롬프트 ChatGPT 이미지 프롬프트 GPT-image-2 프롬프트 OpenAI 이미지 프롬프트 gpt image 2 프롬프트 GPT용 이미지 프롬프트 빌더 OpenAI 이미지 만들기
워크플로우
사용자 자연어 한 줄
↓
[Round 1] AskUserQuestion — 프리셋 선택 (제품샷·인물·일러스트·풍경)
↓
[Round 2] AskUserQuestion — 프리셋별 미세조정 (3~4 슬롯)
↓
[Round 3] AskUserQuestion — 화면비 + 이미지 내 텍스트 유무
↓
[내부] 슬롯 → 6-Block 매핑 (Subject·Action·Scene·Composition·Lighting·Style&Text)
↓
[내부] 같은 슬롯 → Gemini 5-component 변환 + MJ 키워드+파라미터 변환
↓
출력: 3개 모델 프롬프트 코드블록 + 권장 파라미터 + 한국어 해설
실행 규칙
Round 1 — 프리셋 선택 (필수)
AskUserQuestion을 호출해 4개 프리셋 중 1개를 선택받습니다.
| 프리셋 | 적용 케이스 | references |
|---|---|---|
| 제품샷 (권장) | 커머스 상품 사진, 패키지 컷, 보석·시계 클로즈업 | presets/product-shot.md |
| 인물·캐릭터 | 인물 포트레이트, 페르소나 일러스트, 광고 모델 | presets/portrait.md |
| 일러스트·아트 | 카드뉴스 일러스트, 책 표지, 컨셉 아트 | presets/illustration.md |
| 풍경·환경 | 배경 이미지, 공간 사진, 시네마틱 배경 | presets/landscape.md |
선택 결과는 Round 2의 질문 세트를 결정합니다.
Round 2 — 프리셋별 미세조정 (3-4 질문)
선택된 프리셋의 presets/<name>.md에 정의된 질문 세트를 AskUserQuestion으로 순회합니다. 각 질문은 4 옵션 + Other이며, 첫 번째 옵션에 (권장) 라벨을 표시합니다.
제품샷 예시:
- 제품·소재 (예: 매트 블랙 세라믹 머그, 우드 트레이 + 가죽 노트북 슬리브)
- 배경·표면 (예: 젖은 슬레이트 카운터, 베이지 리넨, 화이트 스튜디오)
- 조명·시간대 (예: 창문 사이드 라이트 일출, 스튜디오 소프트박스, 골든아워)
- 카메라 앵글·렌즈 (예: 3/4 앵글 50mm, 탑다운 35mm, 매크로 100mm)
What ships with it
9 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.
- 8d ago First seen · 229 lines · 278 tokens per session scan A e0f1037b3f74
media-gpt-image-2-prompt is a skill published in the GitHub repository modu-ai/moai-cowork (300 stars, last pushed 9d ago), licensed Apache-2.0. It adds 278 tokens to every session and 3,792 once invoked, about $0.0014 per session on Opus 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 2026-09-03.
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