How to Write Better AI Image Prompts
The difference between a mediocre AI image and a stunning one is usually the prompt. You don’t need secret keywords — you need structure. Here’s a simple framework that works on almost any text-to-image model, with examples you can copy.
Describe in layers: subject, details, setting, style
Strong prompts move from the most important thing to the least. Start with the subject and what it’s doing, then add appearance details, then the setting, then the style and lighting.
Example: “a young woman with long silver hair, reading a book, sitting by a rain-streaked window, cosy evening light, soft focus, photorealistic.” Each clause adds one clear idea — the model can follow that far better than a vague “a pretty girl reading”.
Be specific where it matters
Vague prompts give vague results. Instead of “a car”, try “a red 1960s convertible parked on a coastal road at sunset”. Specify colour, era, position, time of day and mood when they matter to you.
You don’t have to specify everything — anything you leave out, the model fills in. So only pin down the details you actually care about, and let it surprise you with the rest.
For anime, think in tags
Anime models are trained on tag-style captions (like Danbooru tags), so they respond well to short, comma-separated descriptors: “1girl, solo, blue hair, school uniform, cherry blossoms, looking at viewer”. Free Image Maker converts your plain English into these tags automatically, so you get the benefit without learning tag syntax.
Naming a specific series or character helps too — anime models often know them by their canonical tag.
Use seeds to iterate, not restart
When you get a result that’s close, don’t start over. Lock its seed and tweak one thing in the prompt — change the outfit, the time of day, the expression. Same seed plus a small prompt change keeps the composition while you refine the details.
On Free Image Maker, every image shows its seed. Save the ones that work as presets, or share a link so anyone can reproduce the look.
Common mistakes to avoid
Overloading the prompt: past a point, extra words get ignored (models have a token limit). Lead with what matters. Contradicting yourself: “a minimalist, highly detailed, busy scene” confuses the model. Relying on negatives alone: it’s usually better to describe what you want than to list everything you don’t.
Try a prompt, look at the result, change one thing, try again. Iteration beats the perfect first prompt every time.
Try it yourself — free, no sign-up.
Open the generator →