caveman-compress

You can reduce markdown token usage by compressing natural language into a concise caveman format. This minimizes input token consumption during AI sessions while preserving code blocks, file paths, and technical structure.

Compressing project documentation via a multi-stage validation process ensures headings, code blocks, URLs, and file paths remain unchanged. This caveman-speak conversion achieves approximately 46% token reduction without losing technical structure.

Compressing markdown files to save tokens does not affect code blocks and file paths. The process strictly preserves technical integrity, automatically validating compressed output against the original to ensure structural elements remain identical.

To safely compress a CLAUDE.md file, run a caveman-speak compression skill that provides automated backups for all modified files. It validates compressed output against the original, ensuring instructions remain exactly the same for the AI.

You can use tools leveraging tiktoken and anthropic dependencies to optimize markdown efficiency for large project memory files. They target project documentation, reducing context overhead by approximately 46% while maintaining automated backups.