Show HN: Bright Lines – a fail-closed guard hook for Claude Code (github.com)

A new safety tool called Bright Lines has been introduced for Claude Code, designed to provide a supervised, fail-closed safety net for AI interactions. By copying a single folder into a project, Bright Lines ensures that Claude must seek user approval before performing any action, while flatly denying a list of high-risk operations, such as bulk deletions or network activity. This setup aims to empower users to leverage AI assistance for their work without risking catastrophic errors or data exposure. The significance of Bright Lines lies in its thoughtful architecture, which includes multiple layers of protection against potentially dangerous commands and actions. It implements a guard hook that intercepts calls and can halt processes before they progress, alongside a comprehensive system to check the installation's integrity. Its simplicity—requiring no dependencies outside of the Python standard library—and plain-language documentation make it accessible to users eager to harness AI safely. Overall, this tool reflects a critical step in addressing safety concerns within AI/ML environments, promoting user trust while navigating the complexities of machine-assisted operations.