paper-reading

To turn research papers into structured narrative notes, provide the document to the system and it will extract core narratives, build an evidence table, classify paragraphs, and save outputs to domain-specific folders using templates.

The best way to extract core arguments and supporting evidence is using a narrative-driven workflow that classifies paragraphs into core, support, and connection categories, then builds a structured data table of claims and supporting data.

Yes, you can use template-driven workflows for paper critique and knowledge management by leveraging provided TEMPLATE-*.md files to guide analysis, prompt structured critical thinking, and synthesize follow-up work into archive-ready outputs.

Yes, this paper-reading approach works with articles, reports, and threads by obtaining the source locally, distilling the main story, highlighting key arguments, and organizing notes for quick retrieval across various text sources.

To organize reading notes into domain-specific folders for quick retrieval, the system saves generated narrative-driven reading note packages and structured evidence tables using provided templates during its automated workflow.

Limitations of automating narrative extraction from dense texts include relying on the provided TEMPLATE-*.md files for structure and requiring local source access to classify paragraphs and build the evidence table effectively.