AgentReady is an API toolkit that makes the web readable for AI agents. TokenCut compresses text before it hits GPT-4, Claude, or any LLM to reduce token costs by 40-60%.
AgentReady is a developer-focused API toolkit that makes the web readable for AI agents while dramatically cutting token costs. At its core is TokenCut, a compression engine that reduces prompt size by 40-60% before the text reaches any large language model (LLM) such as GPT-4, Claude, or Llama. The product is designed for engineers building AI-powered applications—chatbots, automation agents, content analysis tools—who want to reduce their OpenAI or Anthropic bills without sacrificing response quality. By adding a single function call, agentready.compress(), developers get the same answers, same streaming behavior, but a significantly lower token count. The toolkit also includes six other utilities—MD Converter, Sitemap Generator, LLMO Auditor, Structured Data, Robots.txt, and Image Proxy—to transform unstructured web content into AI-ready formats. This holistic approach addresses the growing need for cost-efficient, scalable AI infrastructure in production environments.
The core problem AgentReady solves is the sky-high cost of LLM API calls, especially when processing long documents or multi-turn conversations. Every word sent to GPT-4 or Claude costs money, and prompts often contain verbose, repetitive, or non-essential text that doesn't meaningfully contribute to the model's understanding. For teams running thousands of requests daily, these overhead tokens can balloon monthly bills into thousands of dollars. Worse, many developers are forced to manually truncate or summarize inputs, which risks losing critical context and harms accuracy. AgentReady eliminates this trade-off: it intelligently compresses text while preserving meaning, so teams can maintain full context without paying for unnecessary tokens. The result is immediate cost savings—typically 40-60%—without any rewrite of existing code or changes to the underlying LLM.
The first major feature is TokenCut, the flagship compression tool. TokenCut offers three compression levels—light, medium, and aggressive—so developers can balance token savings against verbatim fidelity. It works by identifying and removing redundant phrasing, eliminating filler words, and condensing verbose structures while preserving code snippets, URLs, and numerical data. The compression process happens in under 5 milliseconds overhead, making it negligible in terms of latency. Importantly, TokenCut is model-agnostic: it compresses text before the API call, so the same function works with OpenAI, Anthropic, Llama, or any other provider. This is critical for teams that switch between models or use multiple ones for different tasks. Benchmarks show an average accuracy delta of only 0.4%, meaning the compressed prompt produces essentially the same output as the original.
Publisher
A
admin
Launch Date2026-02-19
Platformweb
Pricingfree