image-prompting

# Image Prompting Most image failures are prompt failures. This skill gives the MCP agent a repeatable structure for turning any user request into a prompt that renders clean typography, preserves layout on edits, and avoids AI slop. Defaults are tuned for **GPT Image 2** (best legible text), with fallbacks for DALL-E 3, Flux, and Nano Banana. ## Quick Decision Table | User wants... | Model | Mode | Size | Cost | |---|---|---|---|---| | Poster / typography-heavy asset | `openai/gpt-image-2` | generate | `1536x1024` or `1024x1536` | ~$0.04 | | Clean product / UI mockup | `openai/gpt-image-2` | generate | `1024x1024` | ~$0.04 | | Photoreal / fashion / editorial | `openai/gpt-image-2` or `black-forest/flux-1.1-pro` | generate | `1024x1024`+ | $0.04–0.06 | | Artistic / stylized / fast | `google/nano-banana` | generate | `1024x1024` | ~$0.01 | | Edit an existing image (localized change) | `openai/gpt-image-2` | edit | match source | ~$0.04 | | Composite from multiple refs | `openai/gpt-image-2` | edit (multi-ref) | match target | ~$0.04 | **Valid GPT Image 2 sizes:** `1024x1024` (square), `1536x1024` (landscape ~3:2), `1024x1536` (portrait ~2:3). ## The 5-Section Prompt Framework Write prompts as **five short blocks separated by blank lines.** This is the single biggest quality lever. ``` SCENE: where/when/background/environment, one or two lines. SUBJECT: the main focus (who/what), described concretely. DETAILS: materials, texture, lighting, camera angle, composition, mo...