Building a Gate to Control Which Files Reach an AI Model's Context

A DEV Community article argues that AI coding tools often send whole repositories to model endpoints using loose globbing and mtime sorting, which can expose secrets like .env files and Terraform state. It proposes a client-side admission gate in the context assembler that decides what may leave the machine. The author classifies files into four buckets: deny, quarantine, admit, and never-read, with path checks applied first as a cheap, high-precision filter. The piece includes a template implementation that the author notes is unaudited and should be reviewed before use. The article also includes a disclosure that it was prepared as part of product outreach for MonkeyCode, an open-source AI development platform.