A new Rust-based CLI tool named urai-ecma has been developed to significantly reduce the token count required to analyze JavaScript and TypeScript codebases for LLMs. By parsing code into Abstract Syntax Trees (ASTs) and semantically distilling them, it can achieve up to an 80% reduction in tokens, down to 36k from 209k in milliseconds. This addresses the problem of 'infinite context' traps, where noisy code obscures critical architectural information and inflates processing costs and time. Developers can expect faster and more accurate LLM code analysis, especially in CI/CD pipelines with token rate limits.
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