Skill UI

This guide addresses the challenges of automating Apple Notes within Continuous Integration (CI) pipelines on macOS. Because standard CI environments restrict TCC (Transparency, Consent, and Control) permissions, direct automation via osascript usually fails. It provides patterns for using mock clients for unit testing and outlines best practices for running real integration tests on self-hosted runners with proper permissions.

This guide provides comprehensive instructions for deploying AssemblyAI-powered transcription services to major cloud platforms like Vercel, Google Cloud Run, and Fly.io. It covers essential steps including secure secret management, setting up webhook endpoints for asynchronous notifications, and implementing streaming token endpoints for real-time client use in production environments.

A comprehensive, production-ready reference architecture for building robust, scalable transcription services using AssemblyAI. This guide demonstrates best practices for layered system design, covering API endpoints, service logic, client management, and infrastructure integration (webhooks, database). It is ideal for designing new high-throughput speech-to-text applications.

A comprehensive setup for creating a fast and reproducible local development loop for building Attio REST API integrations. This guide includes project structure setup, typed client generation, a mock server implementation (using MSW) for offline development, and a full test harness for unit and integration testing. Ideal for developers building complex SaaS integrations.

This structured tutor is designed for medical and health sciences students, covering core areas like anatomy, physiology, pharmacology, and pathology. It moves beyond rote memorization by focusing on case-based learning, systems integration, and understanding underlying mechanisms. By practicing clinical reasoning and differential diagnosis, users can bridge the gap between basic science knowledge and complex clinical application, preparing them for major medical licensing exams.

This skill establishes a comprehensive CI/CD pipeline specifically for Abridge clinical AI integrations using GitHub Actions. It enforces critical healthcare compliance steps, including FHIR R4 resource validation, robust detection of Protected Health Information (PHI) leaks (like SSN), and end-to-end sandbox integration testing. Ideal for deploying secure, compliant AI applications in the healthcare sector.

A comprehensive troubleshooting guide for Abridge clinical documentation integration. Covers common errors in authentication, EHR connectivity, audio streaming, note generation, and FHIR validation. Essential for developers and technical users debugging AI-powered clinical workflows.

This workflow implements Abridge's end-to-end clinical documentation pipeline. It captures ambient audio from patient encounters, performs real-time transcription, utilizes generative AI to structure the medical notes (e.g., SOAP, H&P), generates required medical codes (ICD-10, CPT), and finally inserts the structured data directly into the EHR system. Designed for primary clinical encounters, minimizing manual charting time.

This workflow converts complex clinical encounter notes into plain-language, patient-facing After-Visit Summaries (AVS). It structures key information such as diagnosis, next steps, and medications. The system supports multi-language translation and facilitates pushing the final, readable summary directly to patient portals using FHIR standards.

This guide provides a comprehensive blueprint for deploying the Abridge clinical AI integration to highly secure, HIPAA-compliant cloud infrastructure. It covers best practices for healthcare deployments, including utilizing BAA-covered services (GCP Cloud Run), robust secret management via GCP Secret Manager, and implementing VPC-restricted networking for maximum data security.

This minimal working example demonstrates Abridge's ambient AI clinical documentation capabilities. It simulates a complete patient encounter session, allowing users to submit transcripts and receive a highly structured clinical note. Ideal for testing EHR connectivity, verifying AI workflow, or learning how structured medical data (SOAP notes, ICD/CPT codes) is automatically generated from free-text conversation.

This guide details the process of setting up authentication and integration credentials for the Abridge clinical AI platform. It covers prerequisites for connecting to major EHR systems (Epic, Athena) using FHIR R4 APIs and implements OAuth 2.0 (SMART on FHIR) flows, ensuring secure, HIPAA-compliant data handling for ambient documentation.