Negative prompting

Telling the model what to avoid — a tone, a claim, a format, a topic — alongside what to do, so unwanted output is ruled out explicitly.

Last updated: November 9, 2026 · Markdown version

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How to apply it in prompts

Use this concept to reduce ambiguity and improve consistency. If you need strict formatting, combine it with a JSON guide and a per-model template.

Related terms:Constraints Role prompting

Strict JSON Models Packs

What it means

Definition: negative prompting adds explicit exclusions to a prompt ('do not use jargon', 'no bullet lists', 'do not mention pricing').
Why it matters: an exclusion closes off a failure you already know about, such as hype words in ad copy, filler openings or content outside the scope you were given.
How to apply it: keep each exclusion specific and testable, pair it with what to do instead ('no jargon; explain terms in plain words'), and put only the few that matter. A long list of 'don'ts' is hard to follow.
In image prompting, a negative prompt is a separate field that lists things to leave out of the picture; there it is a feature of the tool rather than a sentence in the prompt.

Copy-paste example

Rewrite this product description for a landing page.
Do: plain language, one concrete benefit, max 60 words.
Avoid: superlatives ("best", "revolutionary"), unverifiable claims, exclamation marks.
Instead of hype, state what the user can do with the product.

Description:
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Opens the analyzer with the prompt prefilled.

Open in Promptea

FAQ

Do 'don't' instructions work as well as positive ones?

They work best when paired with a positive alternative. 'Don't be vague' is weaker than 'name the metric, the date and the owner'.

Where should exclusions go in the prompt?

Next to the rules they refine, in a short 'Avoid' list, not scattered through the text.