imagegen

Topics in the source

• Image Generation Skill
• When to use
• Decision tree (generate vs edit vs batch)
• Workflow
• Temp and output conventions
• Dependencies (install if missing)
• Environment
• Defaults & rules

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. 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) 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 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

This is an excerpt. Refer to the complete source and its current requirements.