tilth

Current evidence is limited to a single GitHub repository with 303 stars and 22 forks, lacking any hands-on reports, tutorials, or in-depth community discussion. The sample size is too small to assess reliability or real-world performance, so only experimental use is advisable. tilth is a command-line tool that performs context engineering, trimming codebases to show only the most relevant parts to humans or AI agents, thereby reducing the tokens consumed by large language models and reportedly cutting the cost per correct answer by ~40%. It can be installed via cargo or npx, suggesting a low barrier and open-source nature; no pricing or fees have been observed, so it is conservatively inferred to be free. It suits developers who frequently query LLMs about large codebases and want to control API costs, but it is not for those indifferent to token costs, seeking simple code search, or already relying on polished code navigation tools. The discussion quality is extremely low: the star count is just a hype signal, with no social media reviews, benchmarks, or use-case articles to prove utility.