image-gen

Instructions for generating AI-made character artwork and variations with Google Gemini, using reference images to keep characters and visual style consistent.

In plain words
What is it for?
Use it to create character poses, mascot variations, illustrations, and other image assets for apps, websites, or social media.
Why use it?
It provides a repeatable way to plan image requests, choose references, and prepare the required setup before generating artwork.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/peterkrueck/claude-code-development-kit/image-gen
Any agent
npx skills add peterkrueck/Claude-Code-Development-Kit --skill image-gen
Clone the repo
git clone --depth 1 https://github.com/peterkrueck/Claude-Code-Development-Kit

Made for: Claude Code, Codex.

Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,323 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00064 $0.01323
Opus 5 $0.00032 $0.00661
Sonnet 5 $0.00013 $0.00265
Haiku 4.5 $0.00006 $0.00132

Measured 2d ago against content hash 606239b2406b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

image-gen scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/generate.ts), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/image-gen/SKILL.md · 127 lines

How it starts

The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Image Generation (Gemini)

Generate image variations using Google's Gemini image generation model with reference images for style and character consistency. The model supports up to 14 reference images per request and can maintain consistency across multiple characters.

Prerequisites

  • GEMINI_API_KEY environment variable must be set
  • Deno runtime installed (for the generation script)

Workflow

Step 1 — Understand what the user wants

Clarify the subject, pose, expression, context, and where the asset will be used (app screen, social media, website, etc.). This context helps craft the right prompt and choose the right aspect ratio.

Step 2 — Select reference images

Always use 1-2 reference images for consistency:

  1. Primary reference (always first): The most canonical image of the character/subject. This anchors identity — face shape, color palette, defining features.

  2. Style/pose reference (second, optional): Pick the closest existing approved asset to the target pose. This anchors proportions and art style.

The primary reference anchors identity; the style reference anchors proportions. Both together produce the most consistent results.

Step 3 — Craft the prompt

Write a detailed prompt that describes the exact pose, expression, and style:

  1. Character/subject description — physical traits that define the character (so the model doesn't drift)
  2. Pose and expression — what the character is doing
  3. Style directives — art style, line style, shading approach
  4. Background — color, scene, or transparent
  5. Framing — full body, bust, three-quarter view, etc.

Prompt template:

[CHARACTER_DESCRIPTION]. [POSE_AND_EXPRESSION]. [STYLE_DIRECTIVES]. [BACKGROUND]. [VIEW/FRAMING].

Tips:

  • Be specific about what each hand/arm is doing — vague descriptions lead to random poses
  • Always specify the background explicitly
  • Include style keywords consistently (e.g., "flat color fills", "3D render", "watercolor")

Read the full file on GitHub · 127 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 127 lines · 64 tokens per session scan A 606239b2406b

Subscribe to this mod's changes

image-gen is a skill published in the GitHub repository peterkrueck/Claude-Code-Development-Kit (1,380 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 1,323 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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