Question 1

How does text-to-image character consistency work?

Accepted Answer

Text-to-image consistency relies on providing the model with a reference image URL and specialized parameters (such as --cref URL in Midjourney or LoRA nodes in Stable Diffusion). The generator parses the character features and injects them alongside the new scene prompt, allowing the character to appear in multiple settings and poses.

Question 2

Why does the character's face change slightly across different image generations?

Accepted Answer

AI models add a degree of latent noise during diffusion. To maximize facial consistency, set the character weight parameter (like --cw 100 in Midjourney) to lock hair, clothing, and details. To change clothes while keeping the face identical, reduce the weight to --cw 0 so only the face profile is locked.

Question 3

How do I write prompts for image-to-video generation?

Accepted Answer

When doing image-to-video (I2V) prompting, you upload a source image and write a prompt describing the action rather than the details. Since the video model gets the details from the image, your text should focus on camera instructions (e.g., slow tracking shot, camera dollying left) and motion details (dust motes drifting in sunbeams, hair blowing softly in wind).

Question 4

Why does my code prompt output verbose explanations instead of clean code?

Accepted Answer

Standard LLMs are trained to be conversational, leading to verbose introductions. By using Prompt by Niti's Code Blueprint Reference Mode, the generated prompt forces the system instruction layer to mandate raw, syntax-highlighted code output inside markdown blocks while strictly banning conversational padding.

Question 5

Can I force the copywriting generator to adhere to specific marketing frameworks?

Accepted Answer

Yes! Prompt by Niti's Copywriting Framework Reference Mode allows you to choose templates like AIDA (Attention, Interest, Desire, Action) or PAS (Problem, Agitate, Solution). The engine forces the model to structure the response under bold section headers.

Question 6

How do generator credit tiers work when crafting my prompts?

Accepted Answer

Prompt by Niti's prompt reactor runs on three levels of complexity: Normal (1 credit) focuses on syntax structure and clean layouts (500–700 chars). Super (3 credits) adds advanced target audience persona and tone metrics (800–1000 chars). Power (5 credits) appends multi-phase blueprints, anti-visions, and strict success metrics (1200–1500 chars).

Question 7

Can I use these prompts on Midjourney, Sora, Luma, and Runway?

Accepted Answer

Yes! Prompt by Niti's generated prompts are built using standard syntax and engineering patterns designed to be copy-pasted directly into popular AI systems. Midjourney, Flux, Stable Diffusion, Sora, Kling, Runway Gen-3, and Luma Dream Machine are all fully supported.

Question 8

Can I sell my optimized prompt templates on the marketplace?

Accepted Answer

Absolutely! Prompt by Niti is a marketplace where prompt engineers sell high-quality, verified prompt templates. You earn 80% royalties on every sale, with payments processed securely via Razorpay. Head over to the Sell Prompts page to list your prompts.