Image Generation logo

Image Generation

Organization
hyperfx-ai
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-2.5-flare, gpt-image-2.5-sunburst, 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.

Overview

Publisherhyperfx-ai
Repositorymarketing-skills
Skill nameimage-generation
Stars
107
Forks
21
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hyperfx-ai on GitHub. Read the source before you install it.

Installation

Install the Image Generation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hyperfx-ai/marketing-skills/tree/main/skills/image-generation
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hyperfx-ai/marketing-skills.git /tmp/marketing-skills
mkdir -p .claude/skills
cp -r /tmp/marketing-skills/skills/image-generation .claude/skills/image-generation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Image Generation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Image Generation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Image Generation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.

How to run the tools in this skill

Every tool in this skill is named by its canonical tool name. Run it with the call your surface gives you:

SurfaceFind a toolRun it
Hyper chatCall the tool by its name; search_tools(queries=["<provider> <action>"]) shows its parameters<name>(...)
MCP client (Claude, Cursor, Codex, ChatGPT)search("<what you want to do>"), then describe("<name>")call_read("<name>", {...}), call_write or call_destructive: the one that describe names in call_with
Hyper CLIhyperai search "<what you want to do>", then hyperai describe <name>hyperai call <name> --json '{...}'

If a tool is not found: in Hyper chat, find its toolkit id with discover_toolkits and pass it to enable_toolkit. On an MCP client or the CLI, tell the user which integration to connect in Hyper.

Call shape

python
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", "5:4", "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:

Taskmodel
First-pass concepts / quick ad ideation / everyday generationgpt-image-2.5-flare
Precise edits and branded compositions from reference images, production creativegpt-image-2.5-sunburst
Cheap iteration, image-to-image, the widest aspect ratios (adds 1:4, 1:8, 4:1, 8:1)nano-banana
Readable text inside the image (posters, labels, infographics) or search-grounded scenesnano-banana-pro
Product photography, material/fabric fidelity, accurate spatial depthseedream-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:

  1. Call firecrawl_branding_extract with the URL → returns brand colors, fonts, personality/tone, and saved image files (logo, favicon, og_image).
  2. Optionally firecrawl_urls_scrape with formats=["screenshot"] for visual context.
  3. Write the prompt using the actual hex colors, font names, and tone, and pass the logo file_id in reference_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:

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_ratio to intent (social, print, web).
  • Use quality="high" for production, "draft"/"standard" while iterating.
  • Generated file_ids can be reused as reference_images in later calls.
  • For website brand work, call firecrawl_branding_extract before generating.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Image Generation AI skill do?

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-2.5-flare, gpt-image-2.5-sunburst, 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.

Why use Image Generation on TypingMind?

Because you install it once and use it with any model. Image Generation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Image Generation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hyperfx-ai/marketing-skills/tree/main/skills/image-generation. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Image Generation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Image Generation?

As many as you like. As long as a model supports skills, you can use Image Generation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Image Generation AI skill free?

Yes. It is published on GitHub by hyperfx-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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