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Implements a robust data pipeline for handling large documents with the Grammarly API. This utility manages text chunking to comply with API character limits (max 100k), processes text in manageable segments, and aggregates multiple scoring metrics (like correctness, clarity, and tone) into a single, comprehensive report. Ideal for large-scale content analysis and data ingestion.

This bundle collects comprehensive diagnostic evidence for troubleshooting Grammarly API integration issues. It captures API connectivity status, text check responses, authentication details, and rate limit headers. Use this when encountering persistent errors, preparing detailed support tickets, or performing automated health checks on Grammarly services.

A comprehensive guide for configuring and managing Role-Based Access Control (RBAC) in Grammarly Enterprise deployments. This covers role hierarchies (Org Admin, Team Admin, Member, Guest), implementing secure API access, auditing user permissions, and maintaining compliance standards like HIPAA and SOC 2.

This skill provides a comprehensive set of APIs for advanced writing analysis using Grammarly. It allows users to score text based on engagement, correctness, clarity, and tone. Furthermore, it includes functionality for AI detection and sophisticated plagiarism checking. It is ideal for developers needing to build content verification, grammar-checking, or academic integrity tools.

This comprehensive runbook provides structured procedures for diagnosing and responding to critical failures when integrating with the Grammarly API. It covers various incident types, including full API outages, OAuth token expiration, rate limit storms, and suggestion quality degradation. The guide includes severity classification, diagnostic `curl` commands, detailed playbooks, and post-incident documentation steps to ensure service resilience and minimal downtime.

This guide provides a deep dive into migrating from the deprecated Grammarly Text Editor SDK to the current, server-side REST APIs. It details the architectural shift from client-side embedding to modern API calls, covering how to implement Writing Score (v2), AI Detection (v1), and Plagiarism Detection (v1) using secure token authentication.

This guide details how to configure Grammarly API integration across multiple environments (Development, Staging, and Production). It ensures API credentials are isolated, style guides are managed per tier, and rate limits are respected. It provides setup instructions for mocking, sandbox testing, and robust deployment workflows.

This skill implements comprehensive observability (metrics, logging, and alerting) for Grammarly API integrations. It monitors critical performance indicators such as text check latency (p95), API error rates, suggestion acceptance rates, and token consumption. Use this setup when establishing robust monitoring systems, tracking real-time API performance degradation, or implementing proactive alerting to ensure consistent, high-quality user experiences in writing and editing flows.

This guide provides techniques to optimize Grammarly API interactions, focusing on reducing latency and improving throughput. Learn how to implement efficient caching strategies (like LRU cache) for repeated score checks and how to execute multiple API calls in parallel using Promise.all. Use this when experiencing slow response times or needing cost/performance improvements in Grammarly integrations.

A comprehensive guide and implementation pattern for handling rate limits, backoff, and idempotency when integrating with the Grammarly Text API. It provides a custom rate limiter and robust retry logic to manage API throughput, ensuring reliable processing of high volumes of documents and stable interaction with various endpoints (e.g., writing score, plagiarism checks).

Provides comprehensive guidance for upgrading and migrating between different versions of the Grammarly API. This skill covers version detection, critical schema changes (e.g., score breakdown), migration checklists, and implementing robust rollback strategies for writing analysis, AI detection, and plagiarism checking.

A guide on handling asynchronous operations and event notifications for the Grammarly API. Since Grammarly does not provide native push webhooks, this skill demonstrates techniques for implementing polling mechanisms (e.g., for plagiarism detection) and building a robust event bus to reliably handle streamed results, such as score completion or AI content detection alerts.