Humanizer is a .NET library that provides a comprehensive set of extension methods for converting raw data types (numbers, dates, times, byte sizes, strings, enums, collections) into human-readable, localized text. It supports over 90 locales with full pluralization, ordinalization, inflection, and parsing of number words back to numeric values. The library is designed as a reusable dependency for applications requiring user-friendly formatting. Architecturally, Humanizer follows a strategy/registry pattern: each formatting domain (number-to-words, date humanization, ordinalization, etc.) defines an interface and a default implementation, with locale-specific overrides resolved through a central Configurator. Locale data is defined in YAML files and compiled at build time by a Roslyn source generator into immutable profile classes, keeping runtime algorithms generic and data-driven. The library also includes Roslyn analyzers for API migration and a comprehensive test suite with cross-locale theory tests. Key entry points are extension methods on primitive types (e.g., `42.ToWords()`, `"hello_world".Humanize()`, `DateTime.Now.Humanize()`, `ByteSize.FromBytes(1024).Humanize()`) and the `Configurator` for advanced configuration. The primary data flow is: user calls an extension method → culture resolution → delegation to the appropriate converter/formatter → use of generated profile data to produce localized output. External dependencies are limited to the .NET standard library and CLDR plural rule data.