--- title: Caveman: a Claude Code skill that cuts ~65% of output... description: Caveman is a meta-prompt (Claude Code skill) that forces the model to respond in stripped-down, grammar-free 'caveman' language, reducing output tokens by ~65%... canonical: https://daily.dev/posts/caveman-a-claude-code-skill-that-cuts-65-of-output-tokens-by-making-the-model-talk-like-a-caveman-ecyzepv3c twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Caveman: a Claude Code skill that cuts ~65% of output tokens by making the model talk like a caveman. | daily.dev og:description: Caveman is a meta-prompt (Claude Code skill) that forces the model to respond in stripped-down, grammar-free 'caveman' language, reducing output tokens by ~65%... og:url: https://daily.dev/posts/caveman-a-claude-code-skill-that-cuts-65-of-output-tokens-by-making-the-model-talk-like-a-caveman-ecyzepv3c og:image: https://api.daily.dev/og/posts/ECYzePv3C.png og:image:alt: Caveman: a Claude Code skill that cuts ~65% of output tokens by making the model talk like a caveman. og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Caveman: a Claude Code skill that cuts ~65% of output tokens by making the model talk like a caveman. **[Agentic DevOps](https://daily.dev/sources/agenticdevops)** · [@jklancer](https://daily.dev/jklancer) · 1 min read · 1 upvotes · 0 comments ## Summary Caveman is a meta-prompt (Claude Code skill) that forces the model to respond in stripped-down, grammar-free 'caveman' language, reducing output tokens by ~65% without losing reasoning quality. The key insight is that this isn't just a cost optimization — it's a signal-to-noise ratio improvement for multi-turn agentic workflows, where compressed outputs become cleaner context for downstream prompts. A March 2026 paper supports the idea that brevity constraints can actually improve accuracy on certain benchmarks. Best suited for research, analysis, evals, and agent chains; not recommended for tone-sensitive or customer-facing content. ## Content Sounds like a meme. It isn't. Caveman is a meta-prompt that strips grammar, hedging, and filler from every reply. The reasoning is untouched — only the output is compressed. In testing on a routine workflow: ~800 words → ~250 per reply, no useful information lost. A March 2026 paper, _"Brevity Constraints Reverse Performance Hierarchies in Language Models,"_ found that constraining outputs can actually _improve_ accuracy on certain benchmarks, not just reduce cost. The angle most write-ups miss: This isn't a token-cost optimisation. It's a signal-to-noise optimisation. In multi-turn agentic workflows, every reply becomes context for the next turn. Compressing output raises the SNR of every downstream prompt — automatically. Use for: research, analysis, evals, agent chains. Skip for: creative writing, customer-facing copy, anything tone-dependent. Repo: github.com/JuliusBrussee/caveman ## Similar posts on daily.dev - [Talking to Copilot like a caveman](https://daily.dev/posts/talking-to-copilot-like-a-caveman-u5qsbinrw) · The Art of Simplicity · 1 upvotes · 0 comments - [Why use so many tokens when a few do the trick?](https://daily.dev/posts/why-use-so-many-tokens-when-a-few-do-the-trick--uvekb2vuw) · Product Hunt · 4 upvotes · 1 comments - [So Expensive, A Caveman Can Do It](https://daily.dev/posts/so-expensive-a-caveman-can-do-it-xbgdgzytq) · Hackaday · 4 upvotes · 0 comments - [Headroom vs Caveman: A Practical Guide to Reducing AI Coding Costs](https://daily.dev/posts/headroom-vs-caveman-a-practical-guide-to-reducing-ai-coding-costs-q8vwfnm3b) · Syncfusion · 0 upvotes · 0 comments --- [View this post on daily.dev](https://daily.dev/posts/caveman-a-claude-code-skill-that-cuts-65-of-output-tokens-by-making-the-model-talk-like-a-caveman-ecyzepv3c) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"DiscussionForumPosting","mainEntityOfPage":"https://daily.dev/posts/caveman-a-claude-code-skill-that-cuts-65-of-output-tokens-by-making-the-model-talk-like-a-caveman-ecyzepv3c","headline":"Caveman: a Claude Code skill that cuts ~65% of output tokens by making the model talk like a caveman.","text":"Caveman is a meta-prompt (Claude Code skill) that forces the model to respond in stripped-down, grammar-free 'caveman' language, reducing output tokens by ~65% without losing reasoning quality. 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