---
name: image
license: CC-BY-4.0 (attribution required — Serge Shima, github.com/smixs/visual-skills)
description: >
Image prompting skill for Nano Banana (NBP/NB2) and GPT Image 2.5 (Flare/Sunburst). Writes ready-to-use
prompts with model/quality/size recommendations. Use when: "нарисуй", "сгенерируй
картинку", "image prompt", "промпт для картинки", blog covers, slides, posters,
product shots, UI mockups, storyboards, character sheets, edit/colorize, style transfer,
vision analysis, image-to-prompt, nb, NBP, NB2, gpt-image-2.5, multi-panel grids,
ecommerce product photography, fashion editorial, food/beverage ads, cinematic portraits.
Do NOT use for: video (use video skill), 3D models, audio, non-image tasks.
---
# Image Prompting — Nano Banana & GPT Image 2.5
This skill writes image prompts. It does not generate images. The output is: model name + quality / size / aspect ratio + the prompt itself.
The body of this SKILL.md is intentionally thin so you cannot fake a result by reading it alone. The actual rules — what the models reward, what they punish, how to phrase a 5-slot template, when to add `quality: high`, when to use image grounding — live only in the reference files.
## Route first — is this actually an image-prompt task?
- **Motion, clips, montage** (Seedance, Kling, Veo, any image-to-video): use the sibling `video` skill. This skill's storyboard and keyframe outputs feed it.
- **No idea or script yet** (user wants a concept or an ad scenario, not a picture): if the `creative-director` skill is installed, start there — it develops ideas and scripts for commercials and beyond ([github.com/smixs/creative-director-skill](https://github.com/smixs/creative-director-skill)).
- **A concrete image is needed** — this skill. Continue below.
---
# Mandatory reading order — DO NOT WRITE A PROMPT WITHOUT THIS
Past attempts to write prompts directly from this skill body produced lazy, generic results. Each model has its own physics; common rules collapse into mush when applied without model-specific syntax. Read in this order before producing any prompt:
### Step 1 — always read first → [models.md](references/models.md)
Decide: Nano Banana (NB2 or NBP) or GPT Image 2.5 (Flare for speed, Sunburst for precision edits). The choice changes the prompt syntax fundamentally — natural-language paragraphs vs. labeled 5-slot template, quality settings, which features exist (image grounding only on NB, EXACT TEXT discipline only on GPT Image, etc.).
If the user named a model — confirm and proceed. If not — pick using the table in `models.md`, then state your choice in the output header.
### Step 2 — read **one** model file (the one you picked)
- **Nano Banana** → [nano-banana.md](references/nano-banana.md)
Image grounding for real locations. Extreme aspect ratios (1:8, 8:1, 4:1). Thinking mode. JSON for 5+ elements. Up to 14 reference images. Why you must NOT write `50mm / f-stop / ISO` numbers.
- **GPT Image 2.5** → [gpt-image.md](references/gpt-image.md)
5-slot template (Scene / Subject / Important Details / Use Case / Constraints). Anti-slop banned-words list. `quality: low / medium / high / xhigh / max` as a deliberate fidelity lever. Size constraints (multiples of 16, max 3:1, up to 4K 3840×2160). Two-column edit logic (Change / Preserve / Constraints). Up to 16 reference images with explicit roles.
The model file is non-negotiable. Skipping it is the single biggest cause of weak prompts.
### Step 3 — always read after the model file → [golden-rules.md](references/golden-rules.md)
Universal rules that apply to both models: start with a verb, positive framing, hex colors, quote text, edit don't re-roll, one change per iteration, reference images.
### Step 4 — task-shaped reading (load only what matches the request)
Pick zero or more, depending on what the user asked for:
- Text in image, infographic, diagram, multilingual rendering → [text-rendering.md](references/text-rendering.md)
- Edit existing image (object removal, lighting swap, colorization, restoration, localization) → [editing.md](references/editing.md)
- Character continuity across multiple images / panels → [characters.md](references/characters.md)
- **The image must pass as a real photograph** (portrait, reportage, UGC, casting, product-in-hand) — or the user says the result "looks AI", "too glossy", "not like the reference" → [de-slop.md](references/de-slop.md). Model default priors, banned booster words, capture pipeline instead of adjectives, located imperfections.
- Presentation slides → [slides.md](references/slides.md)
- Sequential narrative (storyboard, comic, panel sequence) → [storyboards.md](references/storyboards.md)
- Sketch → final, wireframes, structural input → [structural.md](references/structural.md)
- 2D → 3D, floor plans, isometric → [dimensional.md](references/dimensional.md)
- **Vision analysis / image-to-prompt / style transfer from a reference image** → [vision-decomposer.md](references/vision-decomposer.md). Load this whenever the user attaches an image and asks to recreate, match, decompose, or transfer its style.
- **Multi-panel compositions** (grids, collages, storyboard sheets in ONE image) → [multi-panel.md](references/multi-panel.md). 9-cell TVC grids, 2x2 portrait grids, 3-panel campaign collages, 4x3 borderless grids, 6-frame cinematic sequences, before/after splits, 12-panel storyboard posters.
- **Industry pattern libraries** — proven prompt templates by vertical. Load the matching file:
- E-commerce product shots → [patterns/ecommerce.md](references/patterns/ecommerce.md)
- Fashion editorial campaigns → [patterns/fashion-editorial.md](references/patterns/fashion-editorial.md)
- Food & beverage advertising → [patterns/food-beverage.md](references/patterns/food-beverage.md)
- Cinematic portraits → [patterns/portrait-cinema.md](references/patterns/portrait-cinema.md)
- Posters & illustration → [patterns/poster-illustration.md](references/patterns/poster-illustration.md). Also holds the Style DNA + Reject Checklist method — how to fix a strong visual style in four lines before generating and how to judge the returned image against it. Usable with any pattern in this list, not only posters.
- Character design (turnarounds, expression sheets, outfit grids) → [patterns/character-design.md](references/patterns/character-design.md)
- UI mockups & social media formats → [patterns/ui-social.md](references/patterns/ui-social.md)
### Step 5 — read for production language → [creative-direction.md](references/creative-direction.md)
Studio-quality vocabulary for lighting design, camera and hardware, color grading and film stock, materiality and texture. Read when you need precise terms beyond what `golden-rules.md` covers.
### Step 6 — read if structuring a complex prompt → [prompt-framework.md](references/prompt-framework.md)
Universal element checklist (subject, context, action, environment, camera, lighting, mood, materials, palette, format), detail modes (concise / standard / verbose / cinematic verbose), parameterized templates, output structure with parameters and exclusions.
---
# Output format
When you return the prompt, structure it like this:
```
Model: <nano-banana-2 | nano-banana-pro | gpt-image-2.5-flare | gpt-image-2.5-sunburst>
Quality: <low | medium | high | xhigh | max> (only for gpt-image-2.5)
Size / Ratio: <e.g. 1536×1024 or 16:9>
Prompt:
<the prompt text, ready to copy>
Notes:
- <anything you inferred or assumed because the user did not specify>
```
For edits, also include an explicit preserve-list (mandatory for gpt-image-2.5, recommended for nano-banana):
```
Change: <one concrete thing>
Preserve: <face, pose, lighting, framing, geometry, ...>
Constraints: <no extra objects, no drift, ...>
```
---
# Final response style
Prefer: ready-to-copy prompts, hex colors, concrete materials, named compositions, model-specific syntax (5-slot for GPT Image, natural prose for Nano Banana).
Avoid: tag soup ("cool, modern, 4k"), vague praise ("stunning, epic, masterpiece" — actively hurts GPT Image 2.5), negative framing ("no people, no cars" — invert to positive), external comparisons ("like Apple ad" — describe the visual properties instead), numerical lens parameters in Nano Banana prompts (it ignores them).
---
*Author: Serge Shima ([t.me/aimastersme](https://t.me/aimastersme) · [sergeshima.com](https://sergeshima.com) · [aimasters.me](https://aimasters.me)) · License: CC BY 4.0 — attribution required · Source: [smixs/visual-skills](https://github.com/smixs/visual-skills)*
