Caveman Claude: Token-Cutting Skill Changes AI Workflows
Custom Claude Code skill forces model to respond in ultra-compressed 'caveman speak', cutting token use by 60-75% while still conveying essential info.
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Why it matters
Significant token savings allow faster, more cost-effective AI workflows
Key Points
- 1Skill strips out pleasantries, hedging, and verbose explanations
- 2Gives Claude a specific communication persona to inhabit
- 3Delivers major token savings for automated AI pipelines
Details
The 'caveman Claude' skill instructs the model to use short, declarative sentences with minimal conjunctions. This 'caveman speak' approach is more effective at reducing token use than simply telling Claude to 'be concise'. Testing shows 60-75% token reductions across common dev tasks like code review and function summarization. The savings can add up quickly, potentially cutting $7,665 per year from API costs for a moderate-volume pipeline.
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