# Imagegen

Use when the user asks to generate or edit images via the OpenAI Image API (for...

- Repository: https://github.com/dp-archive/archive (1107 stars)
- Category: Media
- License: Apache-2.0
- Last updated: 2026-03-04
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add dp-archive/archive --skill imagegen -g -a claude-code -y`
Codex: `npx skills add dp-archive/archive --skill imagegen -g -a codex -y`
Cursor: `npx skills add dp-archive/archive --skill imagegen -g -a cursor -y`
Gemini CLI: `npx skills add dp-archive/archive --skill imagegen -g -a gemini-cli -y`

## Description

Use when the user asks to generate or edit images via the OpenAI Image API (for example: generate image, edit/inpaint/mask, background removal or replacement, transparent background, product shots, concept art, covers, or batch variants); run the bundled CLI (`scripts/image_gen.py`) and require `OPENAI_API_KEY` for live calls.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Image Generation Skill

Generates or edits images for the current project (e.g., website assets, game assets, UI mockups, product mockups, wireframes, logo design, photorealistic images, infographics). Defaults to `gpt-image-1.5` and the OpenAI Image API, and prefers the bundled CLI for deterministic, reproducible runs.

## When to use
- Generate a new image (concept art, product shot, cover, website hero)
- Edit an existing image (inpainting, masked edits, lighting or weather transformations, background replacement, object removal, compositing, transparent background)
- Batch runs (many prompts, or many variants across prompts)

## Decision tree (generate vs edit vs batch)
- If the user provides an input image (or says “edit/retouch/inpaint/mask/translate/localize/change only X”) → **edit**
- Else if the user needs many different prompts/assets → **generate-batch**
- Else → **generate**

## Workflow
1. Decide intent: generate vs edit vs batch (see decision tree above).
2. Collect inputs up front: prompt(s), exact text (verbatim), constraints/avoid list, and any input image(s)/mask(s). For multi-image edits, label each input by index and role; for edits, list invariants explicitly.
3. If batch: write a temporary JSONL under tmp/ (one job per line), run once, then delete the JSONL.
4. Augment prompt into a short labeled spec (structure + constraints) without inventing new creative requirements.
5. Run the bundled CLI (`scripts/image_gen.py`) with sensible defaults (see references/cli.md).
6. For complex edits/generations, inspect outputs (open/view images) and validate: subject, style, composition, text accuracy, and invariants/avoid items.
7. Iterate: make a single targeted change (prompt or mask), re-run, re-check.
8. Save/return final outputs and note the final prompt + flags used.

The rest: https://github.com/dp-archive/archive/blob/HEAD/seed_skills/imagegen/SKILL.md