Skill UI

This skill parses complex, free-text clinical trial eligibility criteria from sources like ClinicalTrials.gov into structured, machine-readable rules. It then evaluates these criteria against a comprehensive patient profile (derived from OpenMed data) to determine potential eligibility. The output provides an explainable verdict (eligible, ineligible, or unknown) for every criterion, serving as a critical decision support tool for clinicians and researchers.

This skill converts free-text radiology narratives (CT, MRI, X-ray, etc.) into structured, machine-readable data. It automatically identifies and segments key report sections (Technique, Findings, Impression) and extracts critical clinical details such as anatomy, measurements, laterality, BI-RADS/Lung-RADS scores, and follow-up recommendations. It is crucial for building structured medical records and decision support systems.

This tool automatically formats Python code using the industry-standard 'black' formatter. It ensures your codebase adheres to consistent style guidelines, improving readability and maintainability across the entire team. Ideal for development workflows and code reviews.

This skill scans a specified local directory, extracts essential metadata from the files, and builds a comprehensive, searchable index. It then securely uploads this generated index to a configured remote search service via HTTP, making local files discoverable across remote platforms.

This skill automatically cleans up and prettifies Markdown documents. It fixes structural inconsistencies such as incorrect heading levels and normalizes various list styles. It is useful for ensuring consistent formatting across large markdown files, optimizing readability, and preparing content for documentation or publishing.