Pattern-based anonymization with custom replacement rules and global options via anon().
NLP-powered entity detection that automatically identifies and redacts sensitive entities without manual pattern definitions.
Specialized anonymization helpers for common data types: ID sequences, date shifting, emails, phone numbers, and distribution-preserving numeric anonymization.
Environment summarization with anon_report() and anon_data_summary() to generate safe structural overviews suitable for sharing in prompts or bug reports.
Interactive Shiny app via run_anon_app() for guided anonymization workflows, pattern preview, and prompt building.
