Skill UI

A comprehensive guide and set of scripts for performing load testing and capacity planning for Anthropic's Claude API. This resource helps developers benchmark performance, anticipate traffic spikes, manage rate limits (RPM/ITPM/OTPM), and implement robust horizontal scaling strategies for mission-critical AI services using Python.

A comprehensive guide and implementation for configuring the CI/CD pipeline for AppFolio property management APIs. It utilizes a two-tier testing strategy: fast, mocked unit tests for quick feedback, and slower integration tests running against the AppFolio sandbox environment on main branch merges. This ensures robust validation of API interactions and prevents contract drift before production.

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.

Provides a robust, iterative development workflow for automating Apple Notes using JXA (JavaScript for AppleScript). This setup includes file-watching hot-reloading for rapid testing and helper functions to simulate note CRUD operations, significantly speeding up the development process.

This guide sets up robust CI/CD pipelines for validating Attio integrations. It combines mocked unit tests (using MSW) for speed and gated live API integration tests for pre-release validation. Use this to ensure complete code reliability and automated quality checks across all development pushes.

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.

A comprehensive tutor designed to build robust statistical thinking. It guides users through the entire data analysis lifecycle, from exploratory data visualization and descriptive statistics to complex hypothesis testing and regression modeling. The focus is on understanding the 'why' and 'how' of statistical logic using real datasets and practical problems, rather than just memorizing formulas. It is tool-agnostic, supporting concepts learned in Python, R, SPSS, or Stata.

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.

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 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).

A comprehensive guide to setting up CI/CD pipelines for Adobe API integrations. It covers secure OAuth credential management, unit testing, secret pattern scanning, and rigorous integration testing within GitHub Actions. Essential for maintaining high code quality in Adobe-integrated SaaS products.

This workflow provides a complete, end-to-end solution for building and deploying robust web scrapers using Crawlee on the Apify platform. It guides users through every stage: defining input schemas, setting up the Actor with a sophisticated router pattern, extracting structured data (e.g., product details), saving results to datasets, and managing the full lifecycle from local testing to cloud deployment via apify-cli.