Stop paying for filler words in every prompt
Large language models bill per token, and your system prompt and instructions are charged on every single request. Wordy boilerplate like “in order to”, “please be aware that” and “it is important to note that” adds tokens without changing what the model does — so it quietly inflates your bill across thousands of calls. Paste your prompt above and the checker flags the worst offenders and shows a leaner rewrite.
How it works
The tool scans your text for a curated list of high-frequency filler phrases that prompt engineers commonly leave in. For each match it suggests a token-lean replacement — “in order to” becomes “to”, “due to the fact that” becomes “because”, and pure padding like “kindly” or “please note that” is simply deleted. It then rebuilds a cleaned-up version of your prompt and estimates the token saving using a standard ratio of about 1.3 tokens per English word. The exact figure depends on your model’s tokenizer, but the relative reduction is what matters for budgeting.
Tips for token-lean prompts
- Be direct. Models follow clear imperatives (“Return JSON”) better than hedged requests (“I would like you to please make sure to return JSON”).
- Cut meta-commentary. Phrases that talk about the instruction (“it should be noted that”) rarely change the output — only the token count.
- Move stable context out. If a long instruction never changes, consider prompt caching so you are not re-billed for it on every call.
- Measure at volume. A 30-token saving on a prompt called a million times a month is 30 million tokens — real money on most pricing tiers.