imagegen

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).

Temp and output conventions

Dependencies (install if missing)

Environment

Defaults & rules

Prompt augmentation

Use-case taxonomy (exact slugs)

Examples

Generation example (hero image)

Edit example (invariants)

Prompting best practices (short list)