Skill UI

A powerful skill utilizing the Google Gemini API to generate high-quality images from text prompts or edit existing photos. It supports various aspect ratios, resolutions (up to 4K), and offers model selection for optimal results, making it ideal for creative design, conceptual visualization, and professional visual content creation.

This guide provides expert advice on positioning, framing, and validating medical imaging AI manuscripts for the MICCAI conference. It helps authors tailor their research to meet the venue's specific requirements, focusing on clinical-task grounding, robust validation, and alignment with core scopes like computational anatomy and image-guided intervention. Essential for optimizing conference submission strategy.

This module converts diverse clinical inputs—including scanned images, faxes, CSV/TSV exports, and C-CDA XML—into a normalized, clean text format (`ExtractedDocument`). It supports on-device OCR (Tesseract/PaddleOCR) and structured redaction for tables. It is the crucial first stage for feeding de-identification and Named Entity Recognition (NER) pipelines.

This skill enables the execution of OpenSquilla agents against complex, real-world software engineering benchmarks (SWE-bench). It runs the entire process—from pulling the necessary Docker image to collecting the patch and running official evaluations—in a containerized environment. Use it to test an agent's ability to solve specific coding issues, benchmark performance across datasets (e.g., verified, multilingual), or verify if a generated patch successfully resolves an instance.