AI Image Generation and Editing
zhayujie/CowAgent
Generates or edits images from text prompts through a Python script that picks an image backend based on which API keys are configured.
막연한 요청을 gpt-image-2(Codex $imagegen) 완성 프롬프트로 컴파일. An agent skill from gongnyang/gongnyang-prompt-kit.
Install Image Prompt
$ npx skills add gongnyang/gongnyang-prompt-kit --skill image-prompt -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gongnyang/gongnyang-prompt-kit image-prompt --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/gongnyang/gongnyang-prompt-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/image-prompt .claude/skills/image-prompt && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "image-prompt" agent skill from https://github.com/gongnyang/gongnyang-prompt-kit/tree/main/skills/image-prompt into .claude/skills/image-prompt/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-prompt", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/gongnyang/gongnyang-prompt-kit/tree/main/skills/image-promptType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add gongnyang/gongnyang-prompt-kit --skill image-prompt -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gongnyang/gongnyang-prompt-kit image-prompt --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gongnyang/gongnyang-prompt-kit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/image-prompt .agents/skills/image-prompt && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "image-prompt" agent skill from https://github.com/gongnyang/gongnyang-prompt-kit/tree/main/skills/image-prompt into .agents/skills/image-prompt/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-prompt", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gongnyang/gongnyang-prompt-kit --skill image-prompt -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gongnyang/gongnyang-prompt-kit image-prompt --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gongnyang/gongnyang-prompt-kit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/image-prompt .cursor/skills/image-prompt && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "image-prompt" agent skill from https://github.com/gongnyang/gongnyang-prompt-kit/tree/main/skills/image-prompt into .cursor/skills/image-prompt/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-prompt", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/gongnyang/gongnyang-prompt-kit.git --path skills/image-prompt--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add gongnyang/gongnyang-prompt-kit --skill image-prompt -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gongnyang/gongnyang-prompt-kit image-prompt --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gongnyang/gongnyang-prompt-kit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/image-prompt .gemini/skills/image-prompt && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "image-prompt" agent skill from https://github.com/gongnyang/gongnyang-prompt-kit/tree/main/skills/image-prompt into .gemini/skills/image-prompt/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-prompt", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install gongnyang/gongnyang-prompt-kit image-promptInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add gongnyang/gongnyang-prompt-kit --skill image-prompt -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/gongnyang/gongnyang-prompt-kit.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/image-prompt .github/skills/image-prompt && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "image-prompt" agent skill from https://github.com/gongnyang/gongnyang-prompt-kit/tree/main/skills/image-prompt into .github/skills/image-prompt/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-prompt", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gongnyang/gongnyang-prompt-kit --skill image-prompt -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install gongnyang/gongnyang-prompt-kit image-prompt --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gongnyang/gongnyang-prompt-kit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/image-prompt .opencode/skills/image-prompt && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "image-prompt" agent skill from https://github.com/gongnyang/gongnyang-prompt-kit/tree/main/skills/image-prompt into .opencode/skills/image-prompt/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-prompt", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
image-prompt- GitHub stars
- 328
- Token cost
- ~1.6k tokens
- SKILL.md length
- 772 words
- Files
- 74 (incl. scripts, references)
- Skills in repo
- 1
- Repo updated
- First seen
- Licence
- MIT
At a glance
막연한 요청을 gpt-image-2(Codex $imagegen) 완성 프롬프트로 컴파일. An agent skill from gongnyang/gongnyang-prompt-kit.
- Works in 5 steps: 빠진 결정(카테고리·컷타입·피사체·스타일·구도·텍스트·AR)은 추론해… → 라우팅 표에서 읽을 파일 결정, 포맷은 §포맷 A/B. → 철칙 9개를 지켜 작성, 끝에 AR 토큰. → …
- Tasks that involve Image generation
- SKILL.md covers 워크플로우, 라우팅 표 (유일 라우팅 지점), 철칙 and 마스터 템플릿 (포맷 A 6섹션), plus 4 more sections
- Calls node
What it does
Image Prompt is an agent skill from gongnyang/gongnyang-prompt-kit. 막연한 요청을 gpt-image-2(Codex $imagegen) 완성 프롬프트로 컴파일. 커버 — 카테고리 C1~C12·화보 Format B·홍보물 P1~P12·타이포 포스터 TP1~TP17·룩 L1~L9·컨셉 축 M/R/X/T·jsonl·검증기. 트리거 — "공냥 프롬프트", "이미지 프롬프트 써줘", "화보 프롬프트", "키아트", "타이포 포스터", "홍보물/판촉물", "표지/앨범커버/북커버", "활자 견본/워드마크", "포스터/카드뉴스/만화", "슬라이드/피피티 이미지", "글자 배치", "프롬프트 jsonl", "컨셉부터 잡아줘", "시안 여러 개". ※ 생성·양산은 [codex-imagegen].
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 75 other files, including scripts and reference files (for example `references/category-patterns.md`, `references/concept-axes.md` and `references/editorial-hwabo.md`).
It sits in Media & Creative, covering Image generation. The repository describes itself as: 막연한 요청을 gpt-image-2 완성 프롬프트로 컴파일하는 Claude Code 스킬 — 네거티브 금지·결과 기반 서술·검증 스크립트·C1~C10. The licence is MIT.
When your agent uses it
- Tasks that involve Image generation
Example prompts
- “프롬프트 jsonl”
- “/image-prompt”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- 빠진 결정(카테고리·컷타입·피사체·스타일·구도·텍스트·AR)은 추론해 채운다. 묻는 건 한글 문구 원문·브랜드명·민감 소재뿐.
- 라우팅 표에서 읽을 파일 결정, 포맷은 §포맷 A/B.
- 철칙 9개를 지켜 작성, 끝에 AR 토큰.
- 고가치 산출물은 응답 전 node scripts/check_prompt.mjs 검증(ok:true).
- 생성 연계 시 컴파일된 프롬프트만 넘긴다(거친 원문 금지).
What it can do on your machine
Read from SKILL.md and the folder at commit fb5f75f. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/, which the agent can run.
Shell commands in SKILL.md call:
node
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Image Prompt loads about 1.6k tokens when it runs, and up to ~49k if it reads all its reference files. Until then it costs about 90 tokens; SKILL.md has 772 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from gongnyang/gongnyang-prompt-kit at commit fb5f75f, republished under its MIT licence (© gongnyang). 772 words, ~1,570 tokens.
Download SKILL.mdSave it as
.claude/skills/image-prompt/SKILL.md (or your agent's skills folder). This skill also uses 73 other files; get the full folder from GitHub.- name
- image-prompt
- description
- 막연한 요청을 gpt-image-2(Codex `$imagegen`) 완성 프롬프트로 컴파일. 커버 — 카테고리 C1~C12·화보 Format B·홍보물 P1~P12·타이포 포스터 TP1~TP17·룩 L1~L9·컨셉 축 M/R/X/T·jsonl·검증기. 트리거 — "공냥 프롬프트", "이미지 프롬프트 써줘", "화보 프롬프트", "키아트", "타이포 포스터", "홍보물/판촉물", "표지/앨범커버/북커버", "활자 견본/워드마크", "포스터/카드뉴스/만화", "슬라이드/피피티 이미지", "글자 배치", "프롬프트 jsonl", "컨셉부터 잡아줘", "시안 여러 개". ※ 생성·양산은 [codex-imagegen].
- version
- 4.0.0
🐾 공냥 프롬프트 킷 VOL.2 — gpt-image-2 프롬프트 컴파일러
모호한 요청을 $imagegen용 완성 한국어 프로덕션 프롬프트로 컴파일한다. 생성·양산은 [codex-imagegen](1장은 codex 직접).
워크플로우
- 빠진 결정(카테고리·컷타입·피사체·스타일·구도·텍스트·AR)은 추론해 채운다. 묻는 건 한글 문구 원문·브랜드명·민감 소재뿐.
- 라우팅 표에서 읽을 파일 결정, 포맷은 §포맷 A/B.
- 철칙 9개를 지켜 작성, 끝에
AR토큰. - 고가치 산출물은 응답 전
node scripts/check_prompt.mjs검증(ok:true). - 생성 연계 시 컴파일된 프롬프트만 넘긴다(거친 원문 금지).
확장 예: 포스터→C3·화보→C1 B·키아트→C11·아이콘→C9("텍스트 없음")·제품→C4·만화→C10·피피티→C12(16:9).
출력 계약: 단일=본문+끝 AR x:y만(설명 없이) · 다중=엔트리당 Title/Category(Cn)/Cut type/Prompt · 생성 요청=조용히 컴파일 후 툴 호출.
라우팅 표 (유일 라우팅 지점)
| 요청 신호 | 카테고리/포맷 | 읽을 파일 |
|---|---|---|
| 단독 인물 화보·에디토리얼 | C1·Format B | references/editorial-hwabo.md (룩북·시퀀스·패션 21종 +references/style-taxonomy.md) |
| 타이포 포스터·글자가 곧 이미지 | TP1~TP17 | references/typo-poster-router.md→references/typo-poster/TPn-*.md 1개 |
| 활자 견본·글리프 세트·손절단 워드마크·인쇄 그라디언트 금속 | TP15~TP17 | references/typo-poster-router.md→ 해당 TPn-*.md 1개 |
| 홍보판촉물·브랜드 포스터·"디자인 잘된 포스터" | P1~P12 | references/promo-router.md→references/promo/Pn-*.md 1개. 카드뉴스 밀도 문법 금지(미감 사망) |
| 표지 판면(앨범커버·북커버·패키징 라벨)·색면 분할·회화 표지·간판체 콜라주 | P9~P12 | references/promo-router.md→ 해당 Pn-*.md 1개 |
| 포스터·키아트·인포그래픽·카드뉴스·만화·도감·아이콘·뷰티·캠페인·목업 | C2~C11 | references/category-patterns.md 해당 §. C6·C7=밀도 기본값·돌파 전술 §C6 |
| 프레젠테이션·슬라이드 덱 | C12 | references/category-patterns.md §C12 |
| 무드("있어보이게"·"럭셔리"·"영화처럼") | 룩 L1~L9 | references/look-presets.md 프리셋 1개 드롭인 |
| 시안 다변화·양산 컨셉·"차별화"·"컨셉부터" | M/R/X/T축 | references/concept-axes.md 축 1개 변주 |
| 글자 배치·폰트·그리드·밀집 텍스트 | — | references/typography-layout.md |
| 카메라·조명·색 어휘 | — | references/photo-vocab.md |
| jsonl 배치·모델 팩트·완성 예제·codex 골격·8섹션 변형 | — | references/jsonl-and-examples.md |
라우터(P/TP)는 패턴 1개 선택 후 해당 파일 하나만 로드. 복수 행이 동시에 매칭되면 위쪽 행 우선(표 순서 = 우선순위) — 경계 케이스는 각 라우터의 경계·교차 참조 절이 우선한다.
철칙
앞머리
[AR x:y SIZE wxh]브래킷 금지. size는 API 파라미터(jsonlsize)로만, 프롬프트엔 끝AR x:y하나만. 슬롯 토큰([PERSONA_LOCK]류)은 작성 전용 — 잔존=실격(E-SLOT-LEAK).장면 배제는 전부 긍정형 — gpt-image-2는 장면 네거티브를 오히려 렌더한다(군중→"인물 한 명, 단독", 배경→"깨끗한 단색 배경"). 예외는 두 레인뿐, 우회가 아닌 컴플라이언스 스티어링.
티어 조건 허용 문구 Tier-0 기본 항상 all-positive, 부정문 0개 Tier-1 텍스트 가드 렌더 텍스트 있을 때만 화이트리스트 7종: no extra words·no duplicate text·no invented glyphs·no watermark·no logo·no extra text·verbatim, no extra charactersTier-2 화보 레인 명시 선언 시만(휴리스틱 승격 금지) SAFETY_ASSERT(긍정형, 피사체절)+NEGATIVE_TAIL(AR 직전 1회) 페어 구조 Tier-1 결합 공식(유일 방출형):
All text appears once, perfectly legible — no duplicate text, no extra words, no invented glyphs, no watermark.Tier-2 고정 문자열·페어 규칙(순서 보존 부분집합·tail 단독 금지) 정본 =references/editorial-hwabo.md§3(여기 안 싣음).Negative:라벨은 전 티어 금지(E-NEG-SECTION).빼려는 것 레인 장면 요소(사람·사물·배경·소품) 긍정형 재서술(Tier-0) 텍스트 렌더 결함(중복·유령·워터마크) Tier-1 화이트리스트 정책 안전 단언(화보) Tier-2 페어 SD-era 폐기 어휘 금지.
masterpiece/best quality/8k/4k/uhd/trending on artstation/ultra-detailed/highly detailed/sharp focus, 가중치(word:1.3),--ar/--v, 본문§, 빈 형용사(멋지게/감성적으로/고급스럽게/세련되게/beautiful/stunning). 무대 지정("어워드 수준/전문가처럼/최고급")도 동급, 기준이 프롬프트 밖. 수치(여백 %·60/30/10·위계 단수)·몸 반응·구체 예시로 환원(concept-axes.md §죽은 단어 환원).장비 스펙→결과로 환원. EXIF·장비명 대신 "shallow DoF, background falls off softly"·"warm key + cool rim". (패션
Lens character:·Director signature:는 결과+앵커라 예외.)수치는 박는다. HEX 팔레트(컷당 3~5색), 켈빈,
key:fill 1:2비율.1행 = 1컷 = 1 호출. 한 캔버스 그리드/매트릭스 금지, 여러 컷은 N행.
이상적 피부 금지 → "natural skin texture, visible pores, subtle film grain".
실재 상표·인물 참조 금지, 가상 브랜드/페르소나로.
생성 후 글자 후처리 절대 금지. 텍스트는 프롬프트로 이미지 안에서 렌더(따옴표 카피+롤라벨+자유 작성 존). PNG 위 코드 합성(PIL·ImageMagick·SVG/HTML·캔버스) 일절 금지, 폰트·커닝·톤이 겉돈다. 글자 오류는 프롬프트 수정 후 재생성(타이포 구체화→
2048x2048+quality high→카피 축소 순).
Show full SKILL.md (275 more words)Show less
마스터 템플릿 (포맷 A 6섹션)
순수 서술+HEX. 핵심 시각정보 최상단(첫 섹션=attention 최강). 헤더 # 1. Scene OK, 본문 § 금지.
| # | 섹션 | 무엇을 / 분량 |
|---|---|---|
| 1 | Scene | 누가·무엇이·어디서·무엇을. 핵심 먼저. 60~120어 |
| 2 | Camera | 시점·거리·렌즈 character(결과 서술). 15~30어 |
| 3 | Lighting | 방향·soft/hard·그림자·림라이트(장비명 금지). 10~25어 |
| 4 | Color grading | 팔레트 + 색온도 + HEX 3~5개. 10~20어 |
| 5 | Texture/Medium | 매체·질감·표면 반응·후처리. 10~20어 |
| 6 | Text-in-image (선택) | "따옴표 카피" + 폰트·크기·위치 + legibility 1회. 0~25어 |
| — | 트레일링 | 끝에 AR x:y 토큰만 |
포맷 A / 포맷 B
- 포맷 A — 라벨 6섹션(위 표): 구조물 전반(포스터·키아트·인포그래픽·도감·카드뉴스·만화 등).
- 포맷 B — 화보 플랫 콤마형 단문: 라벨 없이 콤마 한 문단, 350~450자, 기본 AR
2:3(1024x1536). 슬롯 12종 순서·Tier-2 → editorial-hwabo.md. - 라우팅: 단독 인물 화보/글래머 에디토리얼→B, 그 외 전부→A.
사이즈 락 (codex 러너 6종)
API는 커스텀, codex($imagegen) 경로는 6종만 안전. auto 금지, 챕터 내 통일.
| ar | size | ar | size |
|---|---|---|---|
| 1:1 | 1024x1024 | 16:9 | 1792x1024 |
| 2:3 / 3:4 / 4:5 | 1024x1536 | 9:16 | 1024x1792 |
| 3:2 / 4:3 | 1536x1024 | 밀집/다컷 | 2048x2048 |
2:3만 정확비, 3:4·4:5는 세로 근사. 비지원 값(1024x1280 등)도 가까운 6종으로.
API 하드 제약·투명 배경(1.5 폴백): jsonl-and-examples.md §1.
텍스트 렌더 요점
- 카피는 따옴표 고정+폰트·크기·위치·HEX, 한 줄 한 언어(한글+영문 혼합 금지). 카피 2개↑는 롤 라벨(headline/subhead/callout) 분리, 롤별 위치·크기·폰트 지정.
- 렌더 텍스트엔 Tier-1 결합 공식 1회(철칙 #2), 같은 카피 2회 표기=2회 렌더라 금지.
- 한글 스펠아웃 금지(하이픈이 글자로 렌더). 정확도 레버=캔버스 크기(2048 실측 12/12). 영문 조어만 ALL CAPS 최후수단. 라벨엔 실제 문구만.
- 밀집 텍스트(카피 3블록+/소형 글자)는
quality: high+큰 변 페어링(1536/1792·2048x2048). - 국문/영문 혼용: 한국어=서사·무드·문화 명사·한글 카피, 영어=기법 토큰·티어 문구, 하이브리드=한국어 골격+영어 토큰. 상세 photo-vocab.md §8.
검증기
응답·생성 전 node scripts/check_prompt.mjs <file>(stdin 가능).
--tier <0|1|2>강제 /--jsonl레코드 /--apiE-SIZE-LOCK→warning(하드 제약 유지) /--test셀프테스트.- 티어 우선순위:
--tier> jsonltier>lane("editorial"→2) > 휴리스틱(렌더 텍스트→1, 없으면 0). Tier-2는 휴리스틱 승격 불가. - 출력
{ok, format, tier, errors[{code,msg,hint?}], warnings[{code,msg}]}, errors 0=exit 0. - 에러:
E-NEG-TIER(미선언 상위 티어)·E-SLOT-LEAK·E-SIZE-LOCK, 네거티브·앞브래킷·SD어휘·가중치·슬래시플래그·끝AR누락.
© gongnyang, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 73 other files (scripts, references) in skills/image-prompt of gongnyang/gongnyang-prompt-kit.
- SKILL.md
- references/category-patterns.md
- references/concept-axes.md
- references/editorial-hwabo.md
- references/jsonl-and-examples.md
- references/look-presets.md
- references/photo-vocab.md
- references/promo-router.md
- references/promo/P1-typomask.md
- references/promo/P10-solitary-symbol-void.md
- references/promo/P11-painted-crop-cover.md
- references/promo/P12-signage-collage-anchor.md
- references/promo/P2-typo-env.md
- references/promo/P3-crop-occlusion.md
- references/promo/P4-color-campaign.md
- references/promo/P5-meta-ui.md
- references/promo/P6-street-collage.md
- references/promo/P7-editorial-rotate.md
- references/promo/P8-mono-staging.md
- … and 55 more
Open the folder on GitHubat commit fb5f75f
Compare with similar skills
Image Prompt next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Image Prompt this skillgongnyang/gongnyang-prompt-kit | 328 | — | ~1.6k | Automated safety check: Pass | MIT | |
| AI Image Generation and Editingzhayujie/CowAgent | 47k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Structured Image Generationbytedance/deer-flow | 84k | 4 repos | ~2.9k | Automated safety check: Pass | MIT | |
| Canghe Comicfreestylefly/canghe-skills | 461 | 8 repos | ~3.2k | Automated safety check: Pass | None | |
| Generate Imageynulihao/AgentSkillOS | 618 | 10 repos | ~1.7k | Automated safety check: Notes | None | |
| GPT Image Generation CLIwuyoscar/GPT-Image2-Skill | 5.7k | — | ~2.5k | Automated safety check: Notes | MIT |
Similar skills
Structured Image Generation
bytedance/deer-flow
Turns an image request into a structured JSON prompt and runs a bundled Python script to generate the picture, optionally guided by reference images.
Canghe Comic
freestylefly/canghe-skills
Knowledge comic creator supporting multiple art styles and tones.
Generate Image
ynulihao/AgentSkillOS
Generate or edit images using AI models (FLUX, Gemini). An agent skill from ynulihao/AgentSkillOS.
GPT Image Generation CLI
wuyoscar/GPT-Image2-Skill
Generates and edits images with GPT Image 2 or 2.5 through a packaged CLI and a prompt gallery, after settling which model fits the request.
Minimal Zine Poster Generator
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Creates or analyzes quiet, paper-texture zine posters with big negative space, one color accent and experimental type, returning an image prompt and the generated poster.
Related
Categories
Questions about Image Prompt
What does Image Prompt do?
막연한 요청을 gpt-image-2(Codex $imagegen) 완성 프롬프트로 컴파일. An agent skill from gongnyang/gongnyang-prompt-kit. Image Prompt is an agent skill from gongnyang/gongnyang-prompt-kit. 막연한 요청을 gpt-image-2(Codex $imagegen) 완성 프롬프트로 컴파일.
When should I use Image Prompt?
Image Prompt fits situations like: tasks that involve Image generation.
How do I install Image Prompt in Claude Code?
Run `npx skills add gongnyang/gongnyang-prompt-kit --skill image-prompt -a claude-code`. Or copy the skill folder (skills/image-prompt in gongnyang/gongnyang-prompt-kit) into .claude/skills/image-prompt in your project. Claude Code loads it when a task matches its description.
How do I install Image Prompt in Codex?
Run `npx skills add gongnyang/gongnyang-prompt-kit --skill image-prompt -a codex`. Or copy the skill folder (skills/image-prompt in gongnyang/gongnyang-prompt-kit) into .agents/skills/image-prompt in your project. Codex loads it when a task matches its description.
Can I use Image Prompt in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gongnyang/gongnyang-prompt-kit --skill image-prompt -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/image-prompt, .gemini/skills/image-prompt, .github/skills/image-prompt and .opencode/skills/image-prompt in your project.
What does Image Prompt need to run?
Going by SKILL.md and its folder, Image Prompt needs the command-line tools its instructions call (node).
Does Image Prompt access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Image Prompt safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Image Prompt use?
Image Prompt is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Image Prompt use?
About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 47k tokens, read only when the agent opens those files.
What are the alternatives to Image Prompt?
Skills that share tags, products or a category with Image Prompt: AI Image Generation and Editing (zhayujie/CowAgent, 47k stars), Structured Image Generation (bytedance/deer-flow, 84k stars), Canghe Comic (freestylefly/canghe-skills, 461 stars) and Generate Image (ynulihao/AgentSkillOS, 618 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Image Prompt?
gongnyang (a GitHub user) maintains it in gongnyang/gongnyang-prompt-kit, which has 328 GitHub stars. The repository was last updated on July 27, 2026.
Source: gongnyang/gongnyang-prompt-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.