GitHub - JuliusBrussee/caveman: 🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman
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| Source: Mastodon | Original article
A new open‑source tool called **caveman** is turning heads in the developer community by slashing the token consumption of Anthropic’s Claude Code model by up to 70 percent while keeping technical detail intact. The project, posted on GitHub by indie developer Julius Brussee, rewrites Claude Code’s output into a highly compressed “lithic” format that mimics a primitive, grunting style – hence the name – before expanding it back into full code for the user. In its first 24 hours the repository attracted more than 1,300 stars, signalling strong interest from engineers looking to curb the latency and cost of LLM‑driven coding assistance.
The breakthrough matters because Claude Code, recently rolled out as a standard component in ARI’s AI‑native stack for all engineers and consultants, has become a cornerstone of Nordic AI development workflows. Token usage directly translates into API fees and response time, so a tool that can preserve 100 percent of the model’s technical accuracy while discarding the bulk of its verbose output could reshape cost structures for enterprises that rely on Claude Code at scale. By reducing the amount of data sent to and from Anthropic’s servers, caveman also trims network overhead, which is especially valuable in latency‑sensitive CI/CD pipelines.
What to watch next is whether Anthropic embraces the approach or releases its own token‑compression layer, and how quickly IDEs and CI tools integrate caveman into their Claude Code plugins. The rapid uptake suggests that other LLM providers may see similar community‑driven efforts, potentially sparking a broader move toward minimalist prompting as a standard efficiency practice. As we reported on 13 April, ARI’s deployment of Claude Code has already accelerated AI adoption across the region; caveman could now be the next lever that makes that adoption cheaper and faster.
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