Skill UI

This guide details how to configure and authenticate access to the AppFolio Stack API. It utilizes OAuth 2.0 and Basic Authentication credentials (Client ID/Secret) provided through the partner program. It is essential for developers building property management integrations, allowing secure, programmatic access to core data like properties, units, tenants, and leases.

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 workflow establishes a comprehensive local environment for developing and testing clinical AI integrations. It simulates an Electronic Health Record (EHR) using a local HAPI FHIR server and utilizes synthetic patient data. Developers can iterate on complex encounter workflows and API connections safely, without ever using real Protected Health Information (PHI).

Provides structured methods and code examples to optimize Abridge's clinical AI integration for high-volume, enterprise deployments. Focuses on reducing critical latencies across the entire workflow, including audio streaming throughput, note generation pipelines, and secure FHIR push operations, ensuring scalability for large health systems.

A comprehensive guide detailing procedures for upgrading Abridge API versions and migrating between disparate Electronic Health Record (EHR) systems. It covers zero-downtime API versioning strategies (e.g., canary rollout) and outlines high-risk, multi-step procedures for ensuring seamless clinical documentation data continuity during EHR cutovers.

This module provides robust webhook handling for Abridge, managing critical clinical documentation lifecycle events. It ingests events such as note completion, encounter status changes, signing, and quality alerts. By implementing signature verification and idempotency checks, this system ensures reliable, secure integration of clinical data into external platforms like EHRs.

This integration facilitates the secure deployment of Alchemy-powered decentralized applications (dApps) across major cloud platforms like Vercel and Google Cloud Run. It is designed to ensure that sensitive Alchemy API keys are treated as server-side secrets, preventing client-side exposure. Use this when setting up backend services, RPC proxies, or deploying production-grade Web3 applications requiring secure access to blockchain data.

A comprehensive guide to production-ready patterns for Web3 development using the Alchemy SDK. Covers essential architectural components such as multi-chain client factories, response caching mechanisms, type-safe NFT query builders, and robust error classification, ensuring highly scalable and reliable blockchain applications.

This skill provides a comprehensive guide to optimizing Algolia search performance. It covers best practices for reducing record size, selecting optimal searchable attributes, tuning faceting, implementing client-side caching, and configuring replica strategies. Use this guide to minimize search latency and drastically improve the end-user search experience.