DotGhostBoard 2.1 "Leviathan" — Smart Clipboard Tagging & Contextual Actions on Linux (Part 1)

Description and use

Auto‑tagging and contextual actions for the Linux clipboard improve security and workflow efficiency.

Problem

Clipboard tools treat every copied item the same, causing friction for users who work with terminals, editors, and devtools.

Outcome

Auto‑tagging and contextual actions reduce friction and improve security for clipboard content on Linux.

Workflow

• Capture text via Ctrl+C
• Run pre‑compiled regex and heuristics to detect tags
• Store item with tags
• Render UI with contextual actions based on tags

Evidence

Most clipboard tools treat every copied item the same: inert text in a database.

Source

Our constraint was concrete: every classification must run locally, produce deterministic results, and complete in under 1ms for typical clipboard payloads (< 5KB).

Source

The engine lives in core/security/auto_tagger.py. It runs synchronously on every new clipboard item before storage and UI rendering.

Source