What problem does it solve? Deciding which Inkdrop note tags deserve to become dedicated NotebookLM topics is a manual, error-prone judgment call. This Skill automates the analysis by counting notes per tag, checking how additions are distributed across recent months, and outputting a clear verdict: promote, wait, or skip. ## Core Features & Use Cases - Tag-based aggregation: Retrieves all notes for a given tag via the Inkdrop MCP server and computes count, oldest/newest dates, and monthly distribution over the last three months. - Promotion judgment: Applies explicit criteria (3+ notes spread across 2+ of the last 3 months = promote; concentrated or under-counted = wait with a "1 more note" or "1 more month" estimate; otherwise skip). - Full-tag scan mode: When no tag is specified, lists all tags and queries them in parallel to surface every promotion candidate at once. - Use Case: You have dozens of Inkdrop tags and want to know which research topics have accumulated enough sustained notes to justify a new NotebookLM notebook—run the scan and get a prioritized candidate list. ## Quick Start Ask the AI to judge whether the Inkdrop tag "vibe-coding" should be promoted to a NotebookLM topic, or run a full scan across all tags.
