Skill UI

Provides advanced best practices for optimizing Glean's enterprise search performance and scalability. Covers critical techniques such as implementing effective batch sizing, caching strategies, connection pooling, and robust rate limit management to significantly reduce search latency and maintain high-throughput indexing for massive, diverse datasets.

A comprehensive checklist designed to validate the deployment, robustness, and security of an enterprise search system powered by Glean. It covers critical areas such as API integration, secrets management, error handling, monitoring, and permissions, ensuring a stable and reliable user experience in a production setting.

This module provides production-ready patterns for interacting with the Glean enterprise search API. It features a typed client, implementing singleton patterns and robust mechanisms for search and indexing. Key patterns include batch pagination, comprehensive error handling (e.g., retries for rate limits), and a fluent request builder for executing complex, reliable API calls.

A comprehensive guide detailing security best practices for integrating and managing enterprise search with Glean. It covers critical topics such as indexing token management, validating webhook signatures, implementing input validation using Zod, and techniques for data redaction, ensuring that sensitive information is protected across the entire search lifecycle.

Configure comprehensive CI/CD pipelines for integrating Grammarly's text analysis into your development workflow. This setup uses GitHub Actions to run unit and integration tests on pull requests, validating API connectivity, enforcing content quality gates (e.g., minimum grammar scores), and ensuring documentation quality before merging to the main branch.

Skills this deployment guide covers building, configuring, and deploying a containerized Grammarly writing assistant service. It provides detailed instructions for production setup, including Docker configuration, environment variable management (for OAuth credentials), health checks, and zero-downtime rolling updates when integrating Grammarly's Text API for grammar, clarity, and tone checking.

This guide provides a comprehensive walkthrough for authenticating and initializing the Grammarly SDK/CLI. Learn how to use OAuth 2.0 Bearer tokens to securely connect to Grammarly's services (including Writing Score, AI Detection, and Plagiarism Detection). Use this skill when setting up a new integration, handling API key configuration, or managing token refreshing in a development project.

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.