Skill UI

A comprehensive workflow designed for clinical professionals to search, retrieve, and synthesize medical evidence. It allows users to query clinical literature with specialized filters (e.g., specialty, evidence level), check potential drug interactions against patient profiles, and look up the latest specialty guidelines from major health organizations (like ACC/AHA, NICE). The output provides structured citations, confidence scores, and evidence grading to support informed clinical decision-making.

This guide provides a comprehensive roadmap for migrating and upgrading integrations with the OpenEvidence clinical AI platform. It addresses critical API changes, such as schema restructuring (e.g., flat answers to structured evidence), version detection, and updated citation formats. Developers can use this knowledge to implement robust migration logic, ensuring that downstream clinical applications maintain high levels of accuracy and safety when accessing evolving medical evidence.

This skill provides a robust, systematic framework for evaluating the rigor of scientific claims and research studies. It guides users in assessing experimental design validity, detecting various biases (selection, confounding, publication), and evaluating statistical evidence. By applying established grading standards like GRADE and Cochrane Risk of Bias, it is essential for conducting systematic literature reviews, peer reviews, and deep scientific critical analysis.

A highly specialized guide for drafting a rebuttal letter following a revise-and-resubmit (R&R) at top-tier economics journals. It provides a structured, point-by-point framework for professionally conceding, refuting, or upgrading evidence in response to highly technical peer reviewer comments (e.g., identification, modern DID, inference).