imagegen

imagegen is a skill for Codex from PracticalSwan/agent-skills. It costs 75 tokens per session (6,023 once invoked), scanned A, a copy of imagegen, MIT.

A tool for creating or editing bitmap images, such as photos, illustrations, textures, sprites, mockups, and cutout graphics.

In plain words
What is it for?
Use it to generate new images, edit references, or create visual variants for websites, games, interfaces, and other projects.
Why use it?
It helps produce visual assets when code, vector files, or existing images are not enough.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Claude Code; mentions Codex.

Good fit Use it to generate new images, edit references, or create visual variants for websites, games, interfaces, and other projects.

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Install with agentmods
npx agentmods add skills/practicalswan/agent-skills/imagegen
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 PracticalSwan/agent-skills --skill imagegen
Clone the repo
git clone --depth 1 https://github.com/PracticalSwan/agent-skills

Made for: 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.

agentmods badge for imagegen

README.md
[![agentmods](https://agentmods.dev/badge/skills/practicalswan/agent-skills/imagegen/github.svg)](https://agentmods.dev/skills/practicalswan/agent-skills/imagegen)
Your own site
<a href="https://agentmods.dev/skills/practicalswan/agent-skills/imagegen"><img src="https://agentmods.dev/badge/skills/practicalswan/agent-skills/imagegen/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.

agentmods 80×15 button for imagegen

Your own site · 80×15
<a href="https://agentmods.dev/skills/practicalswan/agent-skills/imagegen"><img src="https://agentmods.dev/badge/skills/practicalswan/agent-skills/imagegen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,023 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 81% copy Near-identical to another mod 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 5.1 $0.00075 $0.06023
Opus 5 $0.00037 $0.03011
Sonnet 5 $0.00015 $0.01205
Haiku 4.5 $0.00007 $0.00602

Measured 3d ago against content hash 768651d7777f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

imagegen 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 3d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/image_gen.py, scripts/remove_chroma_key.py), 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.

Origin

This is a copy

81% identical to imagegen — 147 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

imagegen/SKILL.md · 429 lines

How it starts

The opening of the file, as written. The whole thing — 429 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Image Generation Skill

Generates or edits images for the current project (for example website assets, game assets, UI mockups, product mockups, wireframes, logo design, photorealistic images, or infographics).

Host routing

Resolve this before applying the built-in-tool instructions below:

  • Codex: use the built-in image_gen workflow when it is exposed. Preserve the Codex save-path, view_image, chroma-key helper, confirmation, and CLI fallback rules below.
  • Claude Code, including GLM Coding Plan sessions: the GLM endpoint does not provide Codex's built-in image_gen tool. Use an image-generation MCP or tool only when it appears in the active Claude Code tool list. Otherwise, offer the bundled OpenAI CLI fallback only after explicit user approval and the normal local OPENAI_API_KEY setup; if neither route is available, stop with a prompt/manual handoff.
  • GitHub Copilot: use a host-exposed image tool or the approved CLI fallback. Do not invent Codex paths or tool names.

All later references to the "built-in" path are conditional on this host check. Do not infer image capability from the model name or API endpoint.

Top-level modes and rules

This skill has exactly two top-level modes:

  • Host image-tool mode (preferred when exposed): Codex built-in image_gen, or an equivalent active host tool that supports the requested operation. Codex's built-in path does not require OPENAI_API_KEY.
  • Fallback CLI mode: scripts/image_gen.py CLI. Use when the user explicitly asks for the CLI/API/model path, or after the user explicitly confirms a true model-native transparency fallback with gpt-image-1.5. Requires OPENAI_API_KEY.

Within CLI fallback, the CLI exposes three subcommands:

  • generate
  • edit
  • generate-batch

Rules:

  • Use the built-in image_gen tool by default for normal image generation and editing requests.
  • Do not switch to CLI fallback for ordinary quality, size, or file-path control.
  • If the user explicitly asks for a transparent image/background, stay on built-in image_gen first: prompt for a flat removable chroma-key background, then remove it locally with the installed helper at $CODEX_HOME/skills/.system/imagegen/scripts/remove_chroma_key.py.
  • Never silently switch from built-in image_gen or CLI gpt-image-2 to CLI gpt-image-1.5. Treat this as a model/path downgrade and ask the user before doing it, unless the user has already explicitly requested gpt-image-1.5, scripts/image_gen.py, or CLI fallback.
  • If a transparent request appears too complex for clean chroma-key removal, asks for true/native transparency, or local removal fails validation, explain that true transparency requires CLI gpt-image-1.5 --background transparent --output-format png because gpt-image-2 does not support background=transparent, then ask whether to proceed. Run the CLI fallback only after the user confirms.
  • The word batch by itself does not mean CLI fallback. If the user asks for many assets or says to batch-generate assets without explicitly asking for CLI/API/model controls, stay on the built-in path and issue one built-in call per requested asset or variant.
  • If the built-in tool fails or is unavailable, tell the user the CLI fallback exists and that it requires OPENAI_API_KEY. Proceed only if the user explicitly asks for that fallback.
  • If the user explicitly asks for CLI mode, use the bundled scripts/image_gen.py workflow. Do not create one-off SDK runners.
  • Never modify scripts/image_gen.py. If something is missing, ask the user before doing anything else.

Read the full file on GitHub · 429 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.

  1. 3d ago Changed · +3 lines 768651d7777f
  2. 4d ago Changed da0725f58163
  3. 7d ago First seen · 426 lines · 75 tokens per session scan A 6ccecc0daa35

Subscribe to this mod's changes

imagegen is a skill published in the GitHub repository PracticalSwan/agent-skills (14 stars, last pushed 3d ago), licensed MIT. It adds 75 tokens to every session and 6,023 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to imagegen, differing in 147 lines, and is treated as a copy.

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