Skill UI

This guide details setting up a robust local development environment for Grammarly API integrations. It covers establishing the project structure, implementing mocked API responses, and utilizing vitest for comprehensive unit and integration testing. Ideal for developers who require a fast iteration cycle or need to configure reliable API test workflows.

This comprehensive checklist guides developers through the necessary steps to deploy a robust and reliable Grammarly API integration in a production environment. It covers critical aspects such as secure credential storage, rate limit handling, implementing text chunking, designing error resilience patterns (circuit breakers, retries), and establishing comprehensive monitoring and alerting systems to ensure high content quality and system uptime.

This skill provides a comprehensive reference architecture and best-practice project layout for integrating Grammarly functionalities into custom applications. It details the separation of concerns, including Content Quality Service, API Client, and specific API calls (scoring, detection, plagiarism). It is essential for developers designing new Grammarly-powered SaaS integrations or establishing consistent architectural standards.

This guide provides production-ready patterns for integrating with the Grammarly API using both TypeScript and Python. It covers essential architectural aspects, including typed client implementation, robust token management (OAuth flow), and efficient text chunking for processing large documents. Use this when building scalable, reliable Grammarly-powered features into your application.

This guide provides essential security fundamentals for integrating with the Grammarly API. It covers secure credential management (client secrets, access tokens), OAuth token handling, webhook signature verification, and data redaction techniques to protect sensitive user content and maintain compliance.

This skill provides the core mechanism for integrating Hex into external data pipelines. It enables triggering, monitoring, and managing Hex projects (e.g., via Airflow or Dagster) programmatically. Users can implement parameterized runs, execute multi-step ETL workflows sequentially, and handle status polling and error management, making it ideal for production data orchestration.

This skill provides programmatic access to manage Hex workspace resources and configure scheduled project runs via the Hex Admin API. It allows users to automate repetitive tasks, monitor project execution status, and manage users, groups, and data connections using external cron triggers or API calls, ensuring robust workflow automation.

A comprehensive guide and toolkit for optimizing Hex platform costs. This resource details strategies for reducing compute expenditure by auditing seat licenses, consolidating data connections, and optimizing notebook run schedules. It includes code examples for implementing result caching and usage monitoring to prevent unexpected billing spikes.

This guide provides a comprehensive walkthrough for setting up and configuring authentication for the Hex SDK/CLI using OAuth 2.0 Bearer tokens. It is essential for developers looking to integrate Hex into a project, allowing programmatic control over triggering project runs, checking status, and managing connections via the Hex API.

A comprehensive guide to setting up a robust local development loop for Hex API orchestration. This includes defining the project structure, creating a typed API client using TypeScript, and implementing mocked unit tests (e.g., using vitest) to ensure fast iteration and reliable testing of data pipelines and external service interactions.

This guide provides techniques to significantly boost performance when integrating with the Hex API. It covers essential optimization strategies such as implementing LRU caching for project lists, running multiple independent jobs in parallel, and adopting adaptive polling intervals to manage API latency and resource usage effectively. Use this when facing slow data retrieval or requiring high-throughput data processing.

This guide provides production-ready patterns for integrating with the Hex platform API using TypeScript and Python. It covers essential best practices like robust retry logic, typed client usage, pipeline orchestration, and Airflow integration, helping developers establish standardized, reliable coding standards for complex Hex workflows.