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Image Gen

Community
notque
image-gen

AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.

Overview

Publishernotque
Repositoryvexjoy-agent
Skill nameimage-gen
Stars
443
Forks
50
Bundled files
6
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.

  • 6 bundled files

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

  • Open source

    Published by notque on GitHub. Read the source before you install it.

Installation

Install the Image Gen 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/notque/vexjoy-agent/tree/main/skills/content/image-gen
  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/notque/vexjoy-agent.git /tmp/vexjoy-agent
mkdir -p .claude/skills
cp -r /tmp/vexjoy-agent/skills/content/image-gen .claude/skills/image-gen
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Image Gen 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 Gen 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 Gen 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-gen

Backend-agnostic image generation: single images, series with anchor-chain consistency, batch pipelines. Two backends: Gemini (API) and Nano Banana (local scripts with post-processing).

Deep References

SignalLoadContent
Gemini backend selectedreferences/backends/gemini.mdModels, env vars, flag table, examples, error codes
Nano Banana needed (post-processing, series, JSON batch, style-match)references/backends/nano-banana.mdSubcommands, flags, aspect ratios, prompt patterns by asset type

Phase 1: Detect Backend

bash
python3 skills/content/image-gen/scripts/detect-backend.py
  • gemini -- load references/backends/gemini.md
  • ask -- no key found; ask the user to set GEMINI_API_KEY

Gate: backend confirmed.

Phase 2: Write Prompt Files

Write all prompts to disk before any API call. Prompt files are the generation record and anchor-chain input for series.

File naming: single prompts/YYYY-MM-DD-{slug}.md, series prompts/{series-name}-01.md through -NN.md.

markdown
---
model: gemini-3-pro-image-preview
aspect-ratio: 1:1
flags: []
---

Full prompt text. Be explicit about subject, style, background, constraints.
bash
mkdir -p prompts

For series: write ALL prompt files before calling any generation script.

Gate: all prompt files written and reviewed.

Phase 3: Select Script

Use caseScriptSubcommand
Single image, Geminiscripts/generate_image.py--prompt
Batch from text file, Geminiscripts/generate_image.py--batch
Single with post-processingscripts/nano-banana-generate.pygenerate
Style match from referencescripts/nano-banana-generate.pywith-reference
Batch from JSON manifestscripts/nano-banana-generate.pybatch
Series (anchor chain)scripts/nano-banana-generate.pygenerate then with-reference
Post-processing onlyscripts/nano-banana-process.pycrop / remove-bg / pipeline

Model selection:

ScenarioModel
Draft, testing, batch, cost-sensitivegemini-2.5-flash-image (2-5s)
Final asset, character art, typographygemini-3-pro-image-preview (~30s)

Aspect ratio by use case:

Asset typeRatio
Sprites, characters, icons1:1
Card art, landscape16:9
Vertical maps, portrait bg9:16
Portrait cards3:4
Wide banners21:9

Generate at the target ratio. Generating 1:1 and cropping to 16:9 loses 56% of pixels.

Gate: script and subcommand identified.

Phase 4: Generate

Use absolute paths for output files. Show full script output.

Anchor-Chain Algorithm (Series)

Character drift occurs when images are generated independently. Prevent it by passing the previous output as --reference:

image-01.png (no ref) -> image-02.png (ref=01) -> image-03.png (ref=02) -> ...
  1. Generate image 1 with no reference.
  2. Use output of image 1 as --reference for image 2.
  3. Continue: each image N references image N-1.

Save originals with --save-original for any batch or expensive generation. Re-processing a saved original is free; re-generating costs quota and may break the chain.

Gate: script exits 0.

Phase 5: Verify and Report

Read the generated image to verify:

  • Subject matches prompt
  • No unwanted watermarks or artifacts
  • Aspect ratio and framing correct
  • No excessive padding or dark borders

If inspection fails: regenerate with adjusted prompt. Report the issue before retrying.

Report: output file path (absolute), dimensions, model, post-processing applied, verification result. Report only what was requested.

Error Handling

ErrorCauseResolution
GEMINI_API_KEY not setMissing env varexport GEMINI_API_KEY=your_key
No image in responseSafety filter or text-only responseAdjust prompt; remove policy-adjacent content
Missing dependency: google-genaiPackage absentpip install google-genai pillow
Rate limit exceeded (429)Too many requestsIncrease --delay; script retries automatically
Content policy violation (400)Restricted contentRephrase using neutral language
Model not foundWrong model stringUse exact strings: gemini-2.5-flash-image or gemini-3-pro-image-preview

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 Gen AI skill do?

AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.

Why use Image Gen on TypingMind?

Because you install it once and use it with any model. Image Gen 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 Gen in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/notque/vexjoy-agent/tree/main/skills/content/image-gen. 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 Gen?

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 Gen?

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

Is the Image Gen AI skill free?

Yes. It is published on GitHub by notque 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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