Multimodal Model Prompt Engineering Expert

The Problem

Multimodal models do not reward the same prompt style. Midjourney depends on word order, --s, and --style raw; DALL-E 3 works better with complete sentences; Stable Diffusion relies on weights and negative prompts; Flux prefers photographic language; and video models such as Seedance 2.0, Kling 3.0, and Veo 3 also require duration, camera movement, action sequence, and lighting. The bottleneck is often not “I cannot describe it,” but carrying one keyword list across incompatible models, then getting unstable composition, broken text, inconsistent characters, or chaotic motion.

How It Works

The skill treats prompt engineering as a repeatable decision process:

• Intent recognition: decide whether the target is artistic creativity, photorealism, text posters, product shots, brand video, character consistency, or Chinese-style aesthetics.
• Model matching: choose the stronger option by task, such as Midjourney for brand style, Flux for realistic photography, DALL-E 3 for natural language and text rendering, Stable Diffusion for local control and LoRA, Nano Banana Pro for multi-character consistency, and Jimeng AI or Tencent Hunyuan for Chinese prompts.
• Prompt generation: build model-specific structure around subject, setting, action, composition, lighting, style, parameters, and negative prompts; for video, include dolly-in, pan, tracking shot, golden hour, and cinematic terms.
• Cross-model conversion: rewrite a prompt from one model to another, such as turning Stable Diffusion weighted tags into Flux photographic description, or expanding a still-image prompt into a video action timeline.
• Iteration and diagnosis: review composition, lighting, text rendering, character consistency, action count, and camera stability, then propose the next revision.

Scope and Caveats

It provides prompt-method and selection guidance rather than replacement for model capability. Model versions, parameter limits, platform permissions, and asset licensing still matter; DALL-E 3, Flux, and GPT Image 2 handle negative prompts or weights differently, and video prompts should limit the number of simultaneous camera and character actions. Use it as a prompt-engineering workbench, not as a guarantee that any model will reproduce the same quality.