Image generation
Generate images through the Hyper MCP with the unified `images_generate` tool — text-to-image, image-to-image, and branded ad creatives — choosing the model (gpt-image-2, nano-banana, nano-banana-pro, seedream-4.5) per task. Use when the user asks to generate an image, create an ad creative, do an image-to-image edit, render text inside an image, or produce a print-quality poster.From its SKILL.md
npx -y skills add hyperfx-ai/marketing-skills --skill image-generationAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
4.1 KB, 888 tokens by cl100k_base, as published. Nobody here has run it
Image Generation
Generate images with the images_generate tool. It handles text-to-image,
image-to-image (pass reference_images), and multi-image composition. By default
(model="auto") it picks the best model for the request; set model to choose one.
Requirements
This skill assumes the Hyper MCP is connected to your
agent so the images_generate tool is available. For brand-consistent ad creative
work, Firecrawl must also be configured under your Hyper integrations.
Call shape
images_generate(
requests=[{"id": "ad1", "prompt": "A polished SaaS ad, clean composition"}],
aspect_ratio="16:9", # "1:1" (default), "9:16", "16:9", "4:5", "2:3", "3:2", "3:4", "4:3", "21:9", ...
quality="standard", # "draft" | "standard" | "high"
n=1, # 1-4 images per request
model="auto", # see "Choosing a model" below
)
- Image-to-image / brand references: put files in the request:
requests=[{"prompt": "Compose into a gift basket", "reference_images": ["file1", "file2"]}]. - Reproducible output: pass
seed=.... - Ground in real-world search: pass
use_search=True. - Do not display image URLs — they render automatically in chat.
Choosing a model
model="auto" is the right default. Override only when the task clearly calls for a
specific model:
| Task | model |
|---|---|
| First-pass concepts / quick ad ideation | gpt-image-2 |
| Image-to-image with references, high-resolution refinement, broad aspect ratios | nano-banana |
| Readable text inside the image (posters, labels, infographics) or search-grounded scenes | nano-banana-pro |
| Product photography, material/fabric fidelity, accurate spatial depth | seedream-4.5 |
See references/image-prompting.md for per-model prompt-writing tips.
Branded / website ad creatives — extract branding first
If the user gives a website URL and wants on-brand creatives:
- Call
firecrawl_branding_extractwith the URL → returns brand colors, fonts, personality/tone, and saved image files (logo, favicon, og_image). - Optionally
firecrawl_urls_scrapewithformats=["screenshot"]for visual context. - Write the prompt using the actual hex colors, font names, and tone, and pass the
logo
file_idinreference_images.
The branding result's file field is a JSON data file, NOT an image — never pass it
as a reference. Only logo.file_id and images.*.file_id are usable images.
Higher-level workflows
For multi-shot product or marketplace work, prefer the workflow tools — they preserve product identity and return structured results:
images_product_photoshoots_create— multi-shot product photography (studio, lifestyle, hero, carousel, ad pack). See references/product-photoshoot.md.images_marketplace_cards_create— marketplace listing image sets (Amazon main + secondary, A+ modules, Shopify). See references/marketplace-cards.md.
Reminders
- Do NOT display image URLs to the user — they show automatically in chat.
- Refine vague prompts unless the user wants verbatim generation.
- Match
aspect_ratioto intent (social, print, web). - Use
quality="high"for production,"draft"/"standard"while iterating. - Generated
file_ids can be reused asreference_imagesin later calls. - For website brand work, call
firecrawl_branding_extractbefore generating.
What ships with it: 3 files
7.7 KB alongside SKILL.md
references/
- image-prompting.md2.2 KB
- marketplace-cards.md2.6 KB
- product-photoshoot.md2.8 KB
Gives 0 of the 12 instructions most images graphics skills give in 888 tokens
Counted across 341 of the 354 authors here whose files we hold, read 2026-09-06
- Generate images via gemini_generate_imagein 14 of 341, across 10 files
- Set the aspect ratio via set_aspect_ratioin 14 of 341, across 10 files
- Verify MCP image tools are available before generatingin 13 of 341, across 9 files
- Show estimated cost before generatingin 13 of 341, across 9 files
- Run the post-generation SEO checklistin 13 of 341, across 9 files
- Structure prompts as subject, setting, style, lighting, compositionin 10 of 341, across 5 files
- Infer the brand strategy before generatingin 9 of 341, across 5 files
- Use at most two logo concept methodsin 9 of 341, across 5 files
- Use one dominant palette with repeating accentsin 9 of 341, across 5 files
- Extract fileKey and nodeId from the Figma URLin 9 of 341
- Read product marketing context before asking questionsin 8 of 341, across 3 files
- Keep the logo simple, symbolic, and ownablein 8 of 341, across 4 files
Said here and by no other author read
- Use model='auto' by default, overriding only for clear model-specific tasks
- Use nano-banana-pro for readable text or search-grounded scenes
- Use seedream-4.5 for product photography and material fidelity
- Set use_search=True to ground output in real-world search
- Call firecrawl_branding_extract before generating branded website creatives
- Write prompts using extracted hex colors, fonts, and tone
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.