/image-prompt
Use when the user wants to turn a short idea into a rich, production-grade image-generation prompt — posters, landing-page or UI mockups, ads, editorial layouts, photoreal scenes, game screenshots, logos, or illustrations. Builds ONE structured, copy-paste-ready prompt optimized
$ npx -y skills add veryCoolTimo/imagegen-skills --skill image-prompt --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/image-prompt
Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when the user wants to turn a short idea into a rich, production-grade image-generation prompt — posters, landing-page or UI mockups, ads, editorial layouts, photoreal scenes, game screenshots, logos, or illustrations. Builds ONE structured, copy-paste-ready prompt optimized
SKILL.md
image-prompt.SKILL.mdname: image-prompt
description: >-
Use when the user wants to turn a short idea into a rich, production-grade
image-generation prompt — posters, landing-page or UI mockups, ads, editorial
layouts, photoreal scenes, game screenshots, logos, or illustrations. Builds ONE
structured, copy-paste-ready prompt optimized for gpt-image-2 by default, following
proven layered-composition patterns (named zones, hex palette, real font references,
mood/finish, IP-safety). Triggers on requests like "сделай крутой промт для постера",
"нужна картинка/постер/лендинг для…", "generate a prompt for a landing hero",
"prompt for an ad / logo / game screenshot".
image-prompt
Turn a one-line idea into a single, gold-quality image-generation prompt. Auto-first: infer everything sensible, output the prompt, let the user redirect in one line.
Workflow
1. **Read the idea.** Extract: subject/brand, any style hints, aspect/format, target model. Invent a fictional placeholder brand name if branding is implied but none given. If the user names a saved style ("in the <name> style", "use preset <name>") or asks to save one ("save this style as <name>"), handle it via **Style presets** below. If the user wants help choosing a look ("help me with the style", "what styles can you do", "в каких стилях можешь"), present the **Style menu** below. If the user supplies an existing image to transform, composite, restyle, localize, or place someone/something into — or wants a poster/ad built around a supplied person or product — that is an EDIT: use **Edit / remix mode** below.
2. **Pick the archetype** using `references/archetypes.md` (poster / landing-hero / product-ad / ui-mockup / photoreal-scene / game-screenshot / infographic / logo / illustration). Use the routing table. If ambiguous, choose the richest layout and note it.
3. **Set defaults** from the archetype: aspect → `size`, `quality`. (See the model adapter.)
4. **Expand into the 9-block skeleton** using `references/anatomy.md`. Skim the matching gold example(s) in `references/gold-examples.md` to calibrate depth and phrasing. Pull fonts + a cohesive hex palette from `references/fonts-palettes.md`. Fill every block: named zones with position/size%/tilt, literal copy in quotes, named fonts, hex palette, mood cluster, finish + quality tag. Photoreal/game ideas use the labeled-block variant.
5. **Format for the target model.** Default `gpt-image-2` → follow `references/models/gpt-image-2.md` (labeled sections, text-in-quotes, CONSTRAINTS block, size/quality). If the user names another model and its file doesn't exist yet, say so and fall back to the rich natural-language style, then proceed.
6. **Output** (see format below): the finished prompt in its own fenced code block, then a one-line assumptions/knobs note underneath.
Auto-first — do NOT interrogate
Produce a full prompt on the first turn. Only ask **one** question if the idea is truly unworkable (e.g. no discernible subject at all). Everything else — archetype, aspect, palette, brand name, copy — you infer and surface in the assumptions line so the user can correct with a single sentence ("make it 9:16", "darker palette", "brand is NOVA").
Model handling
Default target: **gpt-image-2**. When the user names a model, load its adapter and follow it — the 9-block content stays the same; only the rendering (output shape, params/flags, size/ratio) changes.
| Model (match loosely, incl. RU) | Adapter | |---|---| | gpt-image-2 (default), gpt-image-1, gpt-image-1.5, "openai" | `references/models/gpt-image-2.md` | | nano banana pro, gemini 3 pro image, "gemini", "нанобанана" | `references/models/gemini.md` | | midjourney, "mj", "миджорни" | `references/models/midjourney.md` | | flux, flux.2 | `references/models/flux.md` | | ideogram | `references/models/ideogram.md` | | recraft | `references/models/recraft.md` | | reve | `references/models/reve.md` | | universal / unknown tool | `references/models/universal.md` |
If the user names a model with no adapter yet, use `universal` and say so. **Pick by fit** when the user is unsure: text-heavy / infographic / factual → **gemini (Nano Banana Pro)** or gpt-image-2; brand / typography / vector / logo → **recraft**; pure aesthetics → **midjourney**; open-weight / local / hex control → **flux**; strong prompt-adherence + layout editing → **reve**; unknown tool or "just a great prompt" → **universal**.
Style presets (user-local, private)
Presets are saved **styles** (never content) the user has dialed in, stored per-user at `~/.claude/image-prompt/presets/<name>.md` — NOT in this repo, never committed, private to the machine. Create the directory on first save. Each user grows their own set.
- **Save** — on "save this style as <name>" / "запомни этот стиль как …": distill ONLY the
style layer (never subject, copy, or specific zones). Capture the **distinctive signatures that make the style non-generic** — palette + fonts alone flatten the output. Nail: **MEDIUM/technique** (watercolor vs flat vector vs risograph vs 3D render vs photo), **how and WHERE fills are painted** (flat vs mottled/grainy; applied globally vs confined to specific accent elements — apply a texture where the reference uses it, not everywhere), **LINE quality** (loose/varied vs clean/even), **COMPOSITION rhythm** (sparse/airy vs dense; organic vs grid; negative space), and an explicit **AVOID** list of anti-patterns that would drift toward a generic look. When deriving from reference images, name the 2-3 traits that separate this style from a generic version and encode them; if refs are available, sanity-check the intended output against them. A big AI-tell is the model's own default "polished illustration" look — soft digital watercolor gradients, airbrushed bleed, over-clean vector lines, glossy 3D; name these in AVOID and prefer flat color + real (grain/halftone/print) texture + re
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name: image-prompt description: >- Use when the user wants to turn a short idea into a rich, production-grade image-generation prompt — posters, landing-page or UI mockups, ads, editorial layouts, photoreal scenes, game screenshots, logos, or illustrations. Builds ONE structured, copy-paste-ready prompt optimized for gpt-image-2 by default, following proven layered-composition patterns (named zones, hex palette, real font references, mood/finish, IP-safety). Triggers on requests like "сделай крутой промт для постера", "нужна картинка/постер/лендинг для…", "generate a prompt for a landing hero", "prompt for an ad / logo / game screenshot".
image-prompt
Turn a one-line idea into a single, gold-quality image-generation prompt. Auto-first: infer everything sensible, output the prompt, let the user redirect in one line.
Workflow
1. **Read the idea.** Extract: subject/brand, any style hints, aspect/format, target model. Invent a fictional placeholder brand name if branding is implied but none given. If the user names a saved style ("in the <name> style", "use preset <name>") or asks to save one ("save this style as <name>"), handle it via **Style presets** below. If the user wants help choosing a look ("help me with the style", "what styles can you do", "в каких стилях можешь"), present the **Style menu** below. If the user supplies an existing image to transform, composite, restyle, localize, or place someone/something into — or wants a poster/ad built around a supplied person or product — that is an EDIT: use **Edit / remix mode** below.
2. **Pick the archetype** using `references/archetypes.md` (poster / landing-hero / product-ad / ui-mockup / photoreal-scene / game-screenshot / infographic / logo / illustration). Use the routing table. If ambiguous, choose the richest layout and note it.
3. **Set defaults** from the archetype: aspect → `size`, `quality`. (See the model adapter.)
4. **Expand into the 9-block skeleton** using `references/anatomy.md`. Skim the matching gold example(s) in `references/gold-examples.md` to calibrate depth and phrasing. Pull fonts + a cohesive hex palette from `references/fonts-palettes.md`. Fill every block: named zones with position/size%/tilt, literal copy in quotes, named fonts, hex palette, mood cluster, finish + quality tag. Photoreal/game ideas use the labeled-block variant.
5. **Format for the target model.** Default `gpt-image-2` → follow `references/models/gpt-image-2.md` (labeled sections, text-in-quotes, CONSTRAINTS block, size/quality). If the user names another model and its file doesn't exist yet, say so and fall back to the rich natural-language style, then proceed.
6. **Output** (see format below): the finished prompt in its own fenced code block, then a one-line assumptions/knobs note underneath.
Auto-first — do NOT interrogate
Produce a full prompt on the first turn. Only ask **one** question if the idea is truly unworkable (e.g. no discernible subject at all). Everything else — archetype, aspect, palette, brand name, copy — you infer and surface in the assumptions line so the user can correct with a single sentence ("make it 9:16", "darker palette", "brand is NOVA").
Model handling
Default target: **gpt-image-2**. When the user names a model, load its adapter and follow it — the 9-block content stays the same; only the rendering (output shape, params/flags, size/ratio) changes.
| Model (match loosely, incl. RU) | Adapter | |---|---| | gpt-image-2 (default), gpt-image-1, gpt-image-1.5, "openai" | `references/models/gpt-image-2.md` | | nano banana pro, gemini 3 pro image, "gemini", "нанобанана" | `references/models/gemini.md` | | midjourney, "mj", "миджорни" | `references/models/midjourney.md` | | flux, flux.2 | `references/models/flux.md` | | ideogram | `references/models/ideogram.md` | | recraft | `references/models/recraft.md` | | reve | `references/models/reve.md` | | universal / unknown tool | `references/models/universal.md` |
If the user names a model with no adapter yet, use `universal` and say so. **Pick by fit** when the user is unsure: text-heavy / infographic / factual → **gemini (Nano Banana Pro)** or gpt-image-2; brand / typography / vector / logo → **recraft**; pure aesthetics → **midjourney**; open-weight / local / hex control → **flux**; strong prompt-adherence + layout editing → **reve**; unknown tool or "just a great prompt" → **universal**.
Style presets (user-local, private)
Presets are saved **styles** (never content) the user has dialed in, stored per-user at `~/.claude/image-prompt/presets/<name>.md` — NOT in this repo, never committed, private to the machine. Create the directory on first save. Each user grows their own set.
- **Save** — on "save this style as <name>" / "запомни этот стиль как …": distill ONLY the
style layer (never subject, copy, or specific zones). Capture the **distinctive signatures that make the style non-generic** — palette + fonts alone flatten the output. Nail: **MEDIUM/technique** (watercolor vs flat vector vs risograph vs 3D render vs photo), **how and WHERE fills are painted** (flat vs mottled/grainy; applied globally vs confined to specific accent elements — apply a texture where the reference uses it, not everywhere), **LINE quality** (loose/varied vs clean/even), **COMPOSITION rhythm** (sparse/airy vs dense; organic vs grid; negative space), and an explicit **AVOID** list of anti-patterns that would drift toward a generic look. When deriving from reference images, name the 2-3 traits that separate this style from a generic version and encode them; if refs are available, sanity-check the intended output against them. A big AI-tell is the model's own default "polished illustration" look — soft digital watercolor gradients, airbrushed bleed, over-clean vector lines, glossy 3D; name these in AVOID and prefer flat color + real (grain/halftone/print) texture + re
One line in, a gold-quality image prompt out. image-prompt turns a short idea into a structured, copy-paste-ready prompt for any major image model: posters, landing and UI mockups, ads, editorial, game art, logos, infographics.