intake_article

Article verification and insight extraction are automated through a four-step pipeline that validates source quality, tags evidence, considers alternate scenarios, and assesses applicability. Results are stored as markdown files with YAML frontmatter under knowledge/{domain}/.

The best way to save verified articles is using automated intake validation, which extracts decision-ready takeaways with confidence tags and stores them as structured markdown files with YAML frontmatter under a specified knowledge/{domain}/ directory.

Yes, the article intake workflow supports pasted articles, blog posts, and threads. The four-step validation process applies source quality checks and evidence tagging to each content type before storing extracted insights.

Source evaluation works by applying a critical validation step that checks source quality and tags evidence before extracting insights. The pipeline also considers alternate scenarios and assesses applicability to ensure credibility.

No dependencies or extra components are required to run the article intake pipeline. You simply paste an article or blog post to trigger the automated four-step validation and knowledge storage workflow.

Verified insights are stored in markdown format with YAML frontmatter after article intake processing. The structured files are saved directly under the knowledge/{domain}/ directory for auditable knowledge capture.