Prompt Optimizer

Why prompt optimization saves real money

Input tokens are often overlooked in AI cost calculations — teams focus on output length but forget that long system prompts and verbose user instructions add up at scale. At 10,000 requests/day, even a 20% token reduction on a medium-sized prompt can save hundreds of dollars per month.

The Prompt Optimizer identifies the most common token-wasting patterns: filler phrases like "please can you", redundant qualifiers, duplicate sentences, and verbose vocabulary. It produces three variants so you can choose the right trade-off for your use case.

Three optimization strategies

• 🔵Remove Redundancy — Strips filler openers, redundant qualifiers, and duplicate sentences. Safest option that rarely changes meaning.
• 🟣Restructure for Clarity — Reorders the prompt to lead with the core task, removes elaboration based on your quality setting. Better for long, multi-paragraph prompts.
• 🔵Simplify Language — Replaces Latinate and multi-word phrases with direct alternatives. "Utilize" → "use", "in order to" → "to". Typically the highest reduction.

How accurate is the token counter?

The live token counter uses a 4-chars/token approximation, which matches GPT-family tokenization within ±5% for typical English prose. For exact counts, use the OpenAI tokenizer or the OpenAI Tokenizer playground. The approximation is accurate enough for cost estimates and optimization comparisons.