Generate production-ready image prompts for Midjourney and other image models. Use when the user asks to create, refine, translate, critique, or produce vari...
Design & media
GPT Image 2 Prompt Architect
Try itTurn rough image ideas into structured GPT Image 2 prompt packs with subject, composition, text, and revision guidance.
What it does
GPT Image 2 Prompt Architect classifies an image request into one of five formats — text-to-image, reference-image edit, product photo, UI or poster layout, or image-to-video source frame — then asks only for the missing essentials and returns a prompt pack: a brief strategy note, one primary prompt, two or three focused variants, an avoid list, and three concrete revision moves. Each format has a fixed output template, and debugging heuristics address off-brief results, drifting product geometry, wrong text, identity changes, cluttered composition, and weak video source frames. The skill is text-only, with no helper scripts or network calls.
When to use it
- Drafting a structured prompt from a loose image idea
- Building ecommerce or product photo prompts with label and geometry rules
- Editing with a reference image while preserving identity or product details
- Producing posters, UI mockups, or layouts with readable exact text
The skill document
GPT Image 2 Prompt Architect
This skill turns loose creative ideas into cleaner GPT Image 2 prompt packs with stronger subject control, composition, text rendering, reference-image handling, and revision loops.
Canonical links
- Docs: https://gptimg2.art/docs/gpt-image-2-prompt-architect
- Demo: https://gptimg2.art/models/gpt-image-2
- Create: https://gptimg2.art/ai-image
- Prompt gallery: https://gptimg2.art/prompts/gpt-image-2
- Raw SKILL.md: https://gptimg2.art/skills/gpt-image-2-prompt-architect/SKILL.md
- Prompt guide: https://gptimg2.art/blog/gpt-image-2-prompt-guide
- Product photo prompts: https://gptimg2.art/blog/gpt-image-2-product-photo-prompts
- Image-to-video workflow: https://gptimg2.art/blog/gpt-image-2-image-to-video-workflow
Provenance and safety
- Maintained around the public GPTImg2.art prompt workflow, prompt gallery, and documentation on
gptimg2.art. - Text-only skill pack.
- No helper scripts, no local binaries, no required environment variables, and no autonomous network calls.
- It guides prompt design and references public pages only.
When to use
- The user has a rough AI image idea and wants a stronger GPT Image 2 prompt
- The user wants product photos, ecommerce listing images, lifestyle ads, packaging mockups, or detail shots
- The user needs UI mockups, posters, infographics, social media creatives, readable text, or branded layouts
- The user is editing from reference images and needs identity, product, composition, or style preservation
- The user wants source frames, character sheets, product references, or storyboard frames for image-to-video workflows
- The user has unstable image outputs and needs diagnosis plus a cleaner second-pass prompt
When not to use
- The request is mainly about a different model or non-image workflow
- The user only wants final image generation, API integration, payment help, or account support
- The user asks for unsupported model settings, hidden system behavior, or official provider claims
Workflow
- Classify the request:
- text-to-image
- reference-image edit
- product photo or ecommerce visual
- UI, poster, infographic, or readable-text layout
- image-to-video source frame or storyboard
- Extract or ask for only the missing essentials:
- subject or product
- intended use
- composition and camera/framing
- environment or background
- visual style and lighting
- text that must appear exactly
- reference-image constraints
- aspect ratio or output format
- hard negatives and brand safety constraints
- Keep the first draft focused:
- one primary subject or product
- one clear composition rule
- one lighting or style direction
- one concise constraint block
- Return a prompt pack with:
- a brief diagnosis or strategy note
- one primary prompt
- 2 or 3 focused variants
- a short avoid list
- 3 concrete revision moves for the next round
Prompt construction rules
- Prefer concrete visual language over broad style adjectives.
- Name the subject, product, materials, scale, framing, and lighting before adding mood.
- For product photos, preserve label readability, product geometry, material texture, and commercial usability.
- For reference-image edits, state what must remain unchanged before describing what may change.
- For readable text, quote the exact text and keep the layout simple.
- For UI mockups, describe the device, screen type, layout hierarchy, content density, and visual system.
- For image-to-video source frames, prioritize stable identity, clear silhouette, coherent lighting, and simple motion-ready composition.
- Avoid stacking many subjects, styles, camera angles, and layout goals into one prompt.
- Do not invent unsupported model settings.
Output formats
Text-to-image
Goal:
Subject:
Composition:
Environment:
Style and lighting:
Text requirements:
Constraints:
Prompt:
Reference-image edit
Reference anchor:
What must stay stable:
What may change:
Edit direction:
Style and lighting:
Constraints:
Prompt:
Product photo
Commercial goal:
Product anchor:
Hero angle:
Background or scene:
Lighting:
Label and material rules:
Constraints:
Prompt:
UI, poster, or readable-text layout
Format:
Audience:
Layout hierarchy:
Exact text:
Visual system:
Constraints:
Prompt:
Image-to-video source frame
Video goal:
Source frame subject:
Motion-ready composition:
What must remain stable:
Lighting and style:
Constraints:
Prompt:
Debugging heuristics
- If the image is visually attractive but off-brief, rewrite around the intended use first.
- If product geometry drifts, reduce scene complexity and strengthen product anchor language.
- If text is wrong, shorten the text, quote it exactly, and simplify surrounding design.
- If the subject changes identity, state preservation rules before the edit request.
- If the composition is cluttered, reduce secondary objects and specify one dominant framing.
- If the result cannot become a good video source frame, simplify pose, background, and lighting.
Response style
- Be structured and concise.
- Prefer prompt packs over long theory.
- Offer practical variants that test one axis at a time: subject, composition, lighting, style, or constraints.
- When external examples are useful, point the user to the canonical GPTImg2.art pages listed above.
Questions people ask
- Does the skill generate images itself?
- No. It returns prompt packs only; final image generation, API integration, payment, and account support are explicitly out of scope.
- Which output formats does it cover?
- Five — text-to-image, reference-image edit, product photo, UI/poster/readable-text layout, and image-to-video source frame — each with its own fixed template.
- Can it set unsupported model parameters or reveal hidden system behavior?
- No. The skill guides prompt design and points to public pages; it does not invent unsupported settings or claim official provider behavior.
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