[Feature] Automatically analyze token consumption and provide prompt optimization suggestions

[Xiue233]

Based on token consumption and the structural composition of prompts, NexusGate can provide optimization recommendations to help developers adjust prompts and control the cost of large model usage.

For example, highly variable text such as timestamps—which can significantly reduce cache hit rates in large models—should be identified and addressed.

Can NexusGate implement this functionality using standard regex rules, prompts diff, or by leveraging LLM to automatically propose cost-control strategies?