Caveman — Shrink AI agent token usage by making them speak and read like a caveman, cutting costs.
Analyzed by Sai Pavan Gopularam · AI · LLM Utilities · View on GitHub
- Stars: 105932
- Forks: 6127
- Commits last 30 days: 100
- Health: Active (100 commits this month)
- Language: Go
- License: Other
What It Is
Caveman is a tool that makes AI agents (like Claude or Codex) communicate more concisely, both when they speak and when they read. Think of it like a strict editor that removes all the fluff and filler words from an AI's output and input, leaving only the essential information.
This matters because AI models bill by 'tokens' (roughly words). By cutting down on unnecessary verbosity, Caveman drastically reduces the cost of interacting with AI agents, especially for coding tasks where agents often generate lengthy explanations or consume large log files.
License Verdict
Mixed License: MIT (CLI) & BSL-1.1 (Runtime) — Commercial Use of Runtime Restricted • Source Available
The command-line interface (CLI) is MIT licensed, allowing free commercial use. However, the core runtime (proxy) uses the Business Source License (BSL-1.1). Without a specified 'Additional Use Grant' or 'Change Date' in the license text, commercial production use of the runtime component is generally restricted. Founders should consult the full BSL-1.1 license for specific terms and potential commercial licensing requirements before deploying a service based on the runtime.
How to Use It
Caveman offers two main components: a 'skill' (rule file) for concise AI output, and a 'proxy' that shrinks AI input. The skill is a simple `npx` command, while the proxy requires `npm install` and then configuring for your specific AI agent.
Prerequisites:
- Node.js 22.13+
- npm
Estimated setup time: 10 minutes.
npx skills add JuliusBrussee/caveman -g
npm install -g @caveman-ai/cli
caveman setup --install
caveman claude # Example: wrap Claude agentWhat I'd Build With This
AI Agent Token Cost Calculator & Optimizer (micro-saas)
Build a web service where users can paste AI conversation logs or connect via API to analyze token usage and get 'caveman' optimization suggestions. This helps indie developers and small teams identify verbose outputs and project token savings. Market this tool through developer communities and AI-focused forums.
Effort: 1 Week Build Time · Target: Indie Developers, Small Teams · Pricing: $19/mo (basic), $49/mo (pro)
Managed AI Token Compression Proxy (saas)
Offer Caveman's proxy as a managed cloud service. Companies route their AI agent API calls through your service, which transparently compresses inputs and outputs, directly reducing their AI billing. This targets mid-market tech companies with significant AI usage who prefer a hands-off solution. Reach them via AI consulting networks or enterprise dev tool showcases.
Effort: 3 Months Build Time · Target: Mid-Market Tech Companies · Pricing: Usage-based, e.g., $0.001 per compressed token, or $99/mo + usage
White-Label AI Agent Optimization Suite for Platforms (enterprise)
License and integrate Caveman's core technology into larger AI development platforms, IDEs, or internal enterprise developer tools. Provide a white-label solution that allows these platforms to offer token cost savings directly to their users, enhancing their value proposition. This requires direct sales to platform vendors or large enterprises with custom licensing agreements.
Effort: 6 Months Build Time · Target: AI Platform Vendors, Large Enterprises · Pricing: Custom enterprise licensing, e.g., $50k/year + usage
Sai Pavan Gopularam's Take
This project is a masterclass in turning a viral joke into a serious product. The token-saving numbers are compelling, especially for the proxy. I'd estimate a managed proxy service could easily fetch $500k ARR within a year from mid-sized dev shops.
Watch Out For
- BSL-1.1 License for Proxy Runtime: The proxy component is licensed under BSL-1.1, which has restrictions on commercial production use unless specific 'Additional Use Grants' are met or a 'Change Date' has passed. Verify the full license terms for any commercial deployment.
- Quality vs. Compression Trade-offs: While generally effective, some specific use cases (e.g., compressing human prompts or certain HTML content) might not yield savings or could negatively impact AI model performance, as noted in the project's benchmarks.
- Proxy Setup Complexity: The full proxy setup, especially for specific agents or non-Node.js environments, can be more involved than the simple 'skill' installation. It requires `npm` and Node.js 22.13+.
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