review-article

Automated article analysis performs adversarial verification on investigative content, flagging missing sources, factual inaccuracies, and editorial standard violations. You receive structured reports detailing claims verification and source diversity checks.

Source diversity analysis evaluates the range of references cited in an article to ensure a balanced perspective. It checks compliance with investigative journalism standards by auditing voices, analytical claims, and evaluative language.

Run article verification by executing the review command with your target file path, such as `review-article content/articles/your-article.mdx`. Python scripts handle the evidence audit, checking for missing sources and factual issues.

Yes, this adversarial verification process requires uvicorn, uvicorn-gunicorn, and additional Python libraries to run the analysis scripts. These dependencies provide the environment needed for evidence auditing and claims verification.

Yes, adversarial verification identifies factual inaccuracies, missing sources, and editorial compliance issues in your article. It generates a structured verification report to help you resolve analytical claims and evaluative language problems.

Automated verification focuses on structural checks like source diversity, missing citations, and evaluative language patterns. It requires properly formatted article files and depends on Python scripts, meaning it cannot assess subjective narrative quality or off-page evidence.