Skill UI

Provides expert guidance on designing, implementing, and optimizing cutting-edge computer vision pipelines. Expertise spans real-time object detection (YOLO26), advanced promptable segmentation (SAM 3), and leveraging Vision Language Models (VLMs) for complex visual reasoning. Ideal for building high-performance systems in robotics, autonomous vehicles, and industrial inspection, including 3D reconstruction and edge deployment optimization.

Query UCSF’s ZINC22 repository of 230M+ purchasable compounds via the web UI or CartBlanche APIs to fetch IDs/SMILES, run similarity, supplier, or random sampling, and assemble docking-ready libraries for virtual screening.

This specialized AI acts as an auditor for Medical Devices (SaMD) compliance. It reviews critical documentation like Design History Files (DHF) and technical files against major global regulations, including 21 CFR Part 820, IEC 62304, and ISO 13485. It identifies compliance gaps, cites specific regulations, and provides actionable remediation steps to prepare for regulatory audits.

A comprehensive guide and set of detection rules for identifying OS credential dumping techniques (MITRE T1003). It leverages EDR telemetry, Sysmon process access monitoring, and Windows security event correlation to detect attacks targeting LSASS memory, SAM databases, and NTDS.dit files. Essential for proactive threat hunting and incident response.

A comprehensive tool for creating high-quality training datasets for custom object detection and segmentation models. It supports multiple advanced annotation methods including BBox drawing, SAM2 pixel-perfect segmentation, and DINOv3 visual grounding. Features include AI auto-detection, object tracking, and standardized COCO format export, streamlining the entire data pipeline from capture to training.