Panda Static Image Prompt Design

Problem It Solves

Pure text-to-image, reference-image editing, and local outpainting prompts often fail when they stack keywords, mix negative terms, misuse camera parameters, or lose subject consistency across images. Panda Static Image Prompt Design is not an image generator. It turns a visual brief into a reviewable design strategy and then outputs copy-ready prompts for an image model.

How It Works

• Design first, prompt second: It analyzes scene, audience, brand tone, layout hierarchy, color, material, lighting, and mood before drafting language.
• Six-layer prompt structure: It orders content as task -> subject -> scene state -> emotional goal -> visual style -> quality constraints, keeping core information near the beginning.
• Reference-image consistency: It uses @图1 / @图2 style references, locks the subject on the first image, and adds only incremental differences for later images.
• Context-aware camera language: Real photography prompts include shot size, depth of field, composition, angle, focus, perspective, and camera parameters; non-photographic prompts avoid irrelevant lens and aperture terms.
• Clean delivery: It returns a short design summary and a prompt code block, and can run scripts/check_static.py to scan length, negative words, invalid symbols, and placeholders.

Boundaries

Use it for static visual prompts in e-commerce, posters, social media, product imagery, character imagery, illustration, or 3D work. If the goal is to produce final rendered images, video, or a full brand system, pair it with a real generation pipeline and design review workflow.