Telling an image model what you want is only half the job; the other half is telling it what you do not want. Image models have characteristic failure modes — blurred detail, extra limbs, distorted faces, stray text, watermarks — and a negative prompt is the standard way to steer away from them. Rather than typing the same exclusion list from memory every time, this tool builds it from checkboxes covering the most common flaws, plus your own extras. The result is a comma-separated list ready to paste into the negative-prompt field of your image tool. It cannot guarantee a flawless image — negative prompts reduce flaws, they do not eliminate them — but a consistent exclusion list removes the most common disappointments before they happen.
Quick Answer: Enter blurry and low quality checked and the tool returns “blurry, low quality”.
Free Online Tool
Negative Prompt Generator
Build a negative-prompt list for image models from checkboxes — the things you want excluded from the picture.
Negative prompts steer away from common flaws; they cannot guarantee a flawless image.
How to Use the Negative Prompt Generator
- Enter your input in the tool above — for example, blurry and low quality checked.
- Choose any options the tool offers, such as the conversion direction or the settings that fit your case.
- Click the main button to run the tool and read the result it displays.
- Check the result against what you expected, then adjust the input and run it again if needed.
- Copy the output into your own document, code, or configuration wherever you need it.
Worked Example
Try it with blurry and low quality checked: the tool returns “blurry, low quality”. That example is a good first test whenever you use the tool, because it confirms you entered the input in the expected format before you trust it with your real values. This tool is built for building exclusion lists for image generation, and the worked example shows the shape of a correct result so you can recognize a wrong one at a glance.
Key Features
- Runs entirely in your browser — nothing you type is uploaded anywhere.
- Built for building exclusion lists for image generation, with the result shown immediately and in full.
- No account, no sign-up, and no software to install.
- Clear error messages when an input is incomplete or in the wrong format.
- Free to use as often as you like, for study, work, or checking homework.
Best Practices and Tips
- Start with the worked example in the guide, then substitute your own values.
- Double-check units and formats before trusting a result — most tool errors are input errors.
- Keep a note of the exact inputs that produced a result you rely on, so you can reproduce it.
- For anything important, cross-check with a second method or a known test value.
- Bookmark the tool if you use it regularly, so the same workflow is always one click away.
Common Mistakes to Avoid
- Listing everything imaginable, which over-constrains the model and flattens results.
- Negating a concept the model needs, like excluding “dark” from a night scene.
- Copying a result without checking it against a known example first.
- Assuming the tool knows your context — it only sees the values you enter.
When This Tool Helps — and When It Doesn’t
This tool helps most when you need a fast, checkable answer for building exclusion lists for image generation and you can verify the result against a known example. It does not replace professional judgment: for decisions with real consequences, treat the output as one input among several, verify it independently, and remember that the tool can only work with exactly what you enter. Used that way — quick check, verified result, human decision — it saves time without creating false confidence.
Frequently Asked Questions
Do all image tools support negative prompts?
No. Some expose a dedicated field, others accept negative phrasing inside the main prompt, and some ignore it entirely. Check your tool documentation before relying on the list.
Can negative prompts fix a bad positive prompt?
Only partly. They steer away from flaws, but they cannot supply missing subject detail, composition, or style. Fix the positive prompt first, then add exclusions.
Why is “extra limbs” such a common exclusion?
Because hands, limbs, and faces are where image models most visibly fail anatomy. Excluding the failure explicitly is more effective than hoping the model gets it right.
Related Tools
- AI Prompt Builder – Assemble a structured prompt from role, task, context, constraints, and output format
- AI Prompt Enhancer – Rewrite a rough prompt by applying template rules: role, constraints, format, and examples
- Prompt Token Estimator – Heuristic, clearly labeled approximate token estimate for pasted text