🧰 Aura Tools

Shorten Your Prompt, Cut Your Token Cost

Paste your prompt — filler words, redundant phrases and extra whitespace are stripped automatically, so every API call costs less.

Your Prompt

Paste a prompt above to enable this.

How this works — entirely in your browser, nothing is uploaded.

  • Removes filler words — please, kindly, just, basically, actually, very
  • Compresses wordy phrases — “in order to” → “to”
  • Collapses extra whitespace and blank lines

Token counts use the same ~4 chars/token estimate as the LLM Cost Calculator — close, but not an exact provider count.

What gets cut, and what must survive

Most prompts carry a surprising amount of text that costs tokens on every call and changes nothing about the answer.

Three things reliably fall into that category. Politeness — please, thank you, I hope you can help — which a model does not need. Role padding, the "you are a world-class expert with twenty years of experience" opener, where the useful part is the role itself and the superlatives do nothing. And restatement, where the same instruction appears in the opening line and again at the end in different words.

Strip those and a typical working prompt loses somewhere between a quarter and a half of its tokens while producing the same output. On a prompt that runs thousands of times, that is the difference between a bill you shrug at and one you do not.

What looks like padding but is not

Shorter is not always cheaper

Cutting a prompt so far that the model produces a wrong answer you then have to correct costs more than the tokens you saved, because the retry pays for the whole conversation again. Optimise the prompt, run it on a handful of real inputs, and compare the answers before you adopt the short version.

The counting and rewriting here happen entirely in your browser. Nothing you paste is sent anywhere.

Frequently Asked Questions

Quick answers about how this tool works.

How does the prompt optimizer shorten my prompt?

It removes filler words such as please, kindly, just, basically, literally, actually, very and really, compresses wordy phrases like in order to into to, and collapses extra whitespace and blank lines. It does not rewrite your meaning, so the instruction you are giving the model stays intact.

Will shortening a prompt make the answer worse?

Generally no, because the words it strips carry no instruction. Politeness words and filler do not tell a model anything useful. If a phrase genuinely matters to your task, keep it, since you always see the before and after side by side before copying.

Is my prompt sent to a server?

No. The optimizer runs entirely in your browser. Nothing you paste is uploaded anywhere.

How much money does this actually save?

On a single prompt the saving is fractions of a cent. It becomes meaningful when a prompt is reused at scale, for example inside an app or an agent that runs the same system prompt thousands of times a day, where a 30 to 50 percent token cut compounds.