LLM Cost Optimizer

Category: Engineering Domain: AI Cost Management

Overview

The LLM Cost Optimizer skill provides tools for counting tokens, estimating costs across different LLM providers, and optimizing prompts to reduce token usage without sacrificing quality. Essential for teams managing LLM API budgets at scale.

Clarify First

Before estimating or optimizing, settle the inputs below. When one is missing or vague and would change the result, ask about it; when it wouldn't, use a sensible default and say which one you used.

• Input prompt/text: the prompt file or text to count or optimize (the input via --file/--text/--stdin).
• Target models: which models to estimate cost for (sets --models and the pricing comparison).
• Goal: cost estimation vs prompt optimization, and any target reduction (selects token_counter.py vs prompt_optimizer.py and sets --target-reduction).

Ask about the two or three inputs that matter most for this request, not the whole list. If the user wants a result straight away, produce it and state your assumptions at the top.