Skill UI

This skill facilitates the extraction of population-scale (cohort-level) clinical text from Electronic Health Records (EHR) or FHIR data warehouses using the FHIR Bulk Data Access ($export) operation. It manages the asynchronous job kickoff, polling, and downloading of NDJSON files. The resulting data stream is designed to be fed in batches into OpenMed for mandatory de-identification and Named Entity Recognition (NER) analysis.

This skill manages the loading and efficient caching of OpenMed clinical/biomedical Named Entity Recognition (NER) models. Models are downloaded once from the Hugging Face Hub, enabling full offline operation afterward. It supports model reuse across multiple calls, configuring cache directories, specifying devices (CPU/GPU), and handling various model identifiers (registry keys, full HF IDs, or local paths).

This skill generates browser-playable video assets for web pages by acting as an adapter for the OpenRouter API. It manages the entire asynchronous video generation lifecycle, including submitting the job, polling the status, downloading the final MP4 file, and outputting a structured media manifest for web integration. Use this when a local web video asset is required and configuration details are provided.

This command-line tool allows users to upload local files (screenshots, images, PDFs, videos, etc.) directly to GitHub's internal user-attachments endpoint. It outputs a special URL that GitHub automatically renders when pasted into PRs, issues, or comments, facilitating the easy sharing of media and screenshots within development workflows. It also supports downloading existing private attachments.