Caveman can reduce output tokens. That is not the same as reducing your full Claude cost.

The honest answer is conditional but measurable: if your sessions are output-heavy, shorter responses help. If your sessions are input-heavy, the bigger fix is compact memory and cleaner tool context.

Why the headline can mislead.

A 60% shorter answer does not mean a 60% lower bill. Your total usage includes instructions, files, tool results, cached context, and model-specific pricing or subscription rules.

What Coding Memory Lab measures.

The simulator estimates original output tokens, compressed output tokens, visible output savings, and estimated bill impact based on how output-heavy your workflow is.

What to fix first.

Clean your memory files, remove duplicate instructions, export one compact cross-tool pack, and then measure output compression. That is a stronger workflow than a single prompt.