What is image-generation?

An image tool for generating new pictures and changing existing ones with OpenAI image models. It supports edits such as inpainting, restyling, and extending images.

Creating or editing illustrations, logos, icons, mockups, thumbnails, textures, product images, and other visual assets.

It provides a defined process for choosing an image model and producing drafts or final artwork for different quality and cost needs.

image-generation — Skill by ChristophLabestin/image-generator-mcp

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.

Any agent

npx skills add ChristophLabestin/image-generator-mcp --skill image-generation

Clone the repo

git clone --depth 1 https://github.com/ChristophLabestin/image-generator-mcp

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/christophlabestin/image-generator-mcp/image-generation/github.svg)](https://agentmods.dev/skills/christophlabestin/image-generator-mcp/image-generation)

Your own site

<a href="https://agentmods.dev/skills/christophlabestin/image-generator-mcp/image-generation"><img src="https://agentmods.dev/badge/skills/christophlabestin/image-generator-mcp/image-generation/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/christophlabestin/image-generator-mcp/image-generation"><img src="https://agentmods.dev/badge/skills/christophlabestin/image-generator-mcp/image-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,351 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00090	$0.01351
Opus 5.5	$0.00036	$0.00540
Sonnet 5.5	$0.00018	$0.00270
Haiku 4.5	$0.00009	$0.00135

Measured 2mo ago against content hash 298a8660cdfd, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

image-generation 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 2mo ago.

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-generation/SKILL.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Image generation with GPT Image

Images are produced by the image-generator MCP server, which wraps OpenAI's /v1/images endpoints. Three tools: generate_image, edit_image, list_image_models.

Choosing a model

Leave model unset (or "auto") unless you have a reason not to — the server starts at gpt-image-2 and falls back automatically if the key lacks access.

Override when cost or character matters:

Situation	Model
Final artwork, text inside the image, 2K/4K, inpainting	`gpt-image-2`
Lots of images, quality still matters, no 4K needed	`gpt-image-1.5`
Cheap drafts, thumbnails, composition roughs	`gpt-image-1-mini`
User explicitly asks for DALL·E 3	`dall-e-3`

If a call fails with a model error, run list_image_models — it reports which models this API key can actually see — and retry with an available one.

The two-pass workflow

Generation is billed per image and high quality is several times the price of low. For anything non-trivial:

Draft — quality: "low", small size. Show the user, confirm the composition is right.
Final — same prompt, quality: "high", the real size.

Skip the draft pass only for one-off throwaway images or when the user is clearly in a hurry.

Writing the prompt

These models reward long, concrete prose over keyword soup. Cover:

Subject — what it is, in detail.
Composition — framing, camera angle, what's in fore/background.
Style/medium — photograph, 3D render, flat vector, watercolour, and so on. Name a lens and lighting for photographs.
Palette and mood.
Text — any words that must appear go in the prompt verbatim, in quotes. Say where they sit. Keep it short; long strings still come out garbled.
Negatives — state them positively where you can ("an empty desk" beats "no clutter").

Do not silently rewrite what the user asked for. Add craft detail, keep intent.

Sizes and format

1024x1024 square, 1536x1024 landscape, 1024x1536 portrait — the safe set for every model.
gpt-image-2 additionally takes arbitrary sizes: both edges multiples of 16, max edge 3840, aspect ratio under 3:1. Use it for 1920x1080, 2048x2048, 3840x2160.
background: "transparent" with output_format: "png" (or webp) for logos, icons, stickers and anything that gets composited. Every gpt-image model supports this — gpt-image-2, 1.5, 1 and 1-mini were all verified to return a real alpha channel with fully transparent corners. So you can draft transparent assets cheaply on gpt-image-1-mini and only go up for the final. dall-e-3 cannot do transparency at all.
output_format: "jpeg" for photographic images headed for the web.

Read the full file on GitHub · 119 lines

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.

2mo ago First seen · 119 lines · 90 tokens per session scan A 298a8660cdfd

Subscribe to this mod's changes

image-generation is a skill published in the GitHub repository ChristophLabestin/image-generator-mcp (1 stars, last pushed 2mo ago), licensed MIT. It adds 90 tokens to every session and 1,351 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-31.

Creative and media

image-generation next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
image-generationChristophLabestin/image-generator-mcp	Skill	1	2mo ago	MIT	A	90	Claude Code, Codex
imagegenopenai/codex	Skill	134k	today	Apache-2.0	A	113	Codex
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	yesterday	MIT	A	200	Claude Code, Codex
playwright-climicrosoft/playwright	Skill	100k	yesterday	Apache-2.0	A	19	Claude Code
browser-automationopenclaw/openclaw	Skill	394k	today	MIT	A	36	Claude Code
systematic-debuggingobra/superpowers	Skill	314k	4d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	today	MIT	A	95	Claude Code