Library developers often struggle to balance providing sufficient debugging information with remaining unobtrusive to the end user. Traditional logging frameworks are typically designed for applications, forcing library authors to either impose specific configurations or leave users in the dark when troubleshooting complex protocols like ActivityPub. LogTape provides a solution through a hierarchical category system that ensures zero default output unless explicitly enabled by the application developer. By utilizing these categories, frameworks like Fedify can offer granular visibility into specific subsystems, such as HTTP signature verification or JSON-LD processing, without cluttering the console with internal chatter. Additionally, LogTape leverages implicit contexts and asynchronous local storage to enable seamless request tracing across asynchronous boundaries, allowing developers to correlate related logs through unique identifiers automatically. This approach supports modern runtimes including Node.js, Deno, and Bun, providing a consistent logging experience across diverse environments. By prioritizing an opt-in philosophy and structured data, library authors can provide high-quality observability while maintaining a clean developer experience. Adopting this strategy transforms logging from a potential nuisance into a powerful diagnostic tool for complex distributed systems.