Searching files by tags involves locating documents using descriptive keywords you assign, instead of relying on filenames or folder locations. A tag is like a customizable label that groups content based on context, purpose, or attributes, regardless of where the file is stored. This differs from traditional folder searching, which requires navigating a hierarchy, or simple keyword searches within text, which may miss untagged or non-text files.

Common tools supporting tag-based search include photo libraries like Adobe Lightroom (using tags/keywords for shots), document managers such as Evernote (tagging notes for topics like "Project Budget" or "Recipes"), and development platforms like GitHub (tagging repositories or issues). Users in creative fields often tag design assets by client or style, while researchers tag papers by subject area.

Advantages include powerful filtering across storage locations, enhanced discoverability, and flexible organization without duplicating files. A key limitation is reliance on consistent user tagging; inconsistent application reduces effectiveness. While tags simplify personal organization, consider privacy implications if syncing tagged files to cloud platforms. Future improvements involve AI assisting with auto-tagging suggestions and standardization.