CleanPrompt underlines unnecessary prompt text and suggests micro-edits that reduce tokens without changing your intent. Fewer tokens → fewer FLOPs → lower inference energy.
Built for people who care about efficiency and impact.
Red dotted underlines highlight convoluted text that could be simplified.
A tiny popup shows clarity gains and estimated token & energy savings for each edit.
Accept changes inline or keep your original phrasing.
We scan your prompt (client-side) for verbosity, duplication, and formatting bloat.
We show in-place edits with a small popup estimating token and energy savings.
Accept one, all, or none. You’re always in control of meaning and tone.
Inference cost and energy scale roughly with tokens processed. Trimming the prompt often trims energy and latency too. Estimates vary by model and context.
Remove repetition, formatting overhead, and unnecessary text.
Energy & cost often fall ~proportionally with tokens.
Shorter prompts mean faster responses and better UX.
Simpler, clearer prompts improve readability and intent preservation.
Notes: Savings are estimates and depend on model/provider, context size, and conversation history. CleanPrompt focuses on reducing tokens while preserving intent and output quality.
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