process-content

To turn raw pasted text into structured note files, paste your content and request processing. The skill applies semantic segmentation to split passages into distinct ideas, classifies them, and routes them to Template A or B files.

Semantic segmentation for content processing splits input text by meaning rather than by paragraph or word count. This allows one passage containing multiple distinct ideas to become several separate classified records.

You classify and route dictation notes into a knowledge base by pasting them for semantic segmentation. The skill identifies idea types like tasks, predictions, and reading lists, then routes each to the correct destination.

Content processing preserves your exact user language when creating note files. The skill splits and classifies ideas without altering the original phrasing, then validates the template output before saving.

The best way to split one passage into multiple structured records is semantic segmentation. This approach detects multiple ideas within a single block of text, classifies each one, and outputs validated Template A or B files.

You can verify template outputs before they are saved. The skill creates Template A or B files, checks the structured result against validation rules, and presents the output for your approval before saving.