Skill UI

This skill automates the multi-round research review process. It iteratively reviews provided work using advanced AI models (Codex MCP), identifying critical weaknesses, implementing fixes, and re-reviewing until the content achieves a positive assessment or the maximum round limit is reached. Ideal for refining complex academic papers, technical designs, or large codebases that require rigorous, iterative quality assurance.

This skill provides a comprehensive, dual-engine audit for content, covering both Search Engine Optimization (SEO) and Answer Engine Optimization (AEO), along with readability metrics. It generates detailed scores (out of 100) and provides a severity-ranked list of issues (Critical, Important, Polish) with specific, actionable fix instructions. Use it before publishing to ensure content achieves optimal search performance and high engagement.

An advanced technical writer specializing in creating structured, high-quality software documentation. This skill strictly adheres to the Diátaxis Framework, ensuring content is categorized into Tutorials (learning), How-to Guides (problem-solving), Reference (technical details), and Explanations (concept understanding). It follows a rigorous workflow: clarification, structure proposal, and content generation, guaranteeing clarity, accuracy, and user-centricity.

Provides a comprehensive audit of content quality, focusing on E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) signals, readability, and structural integrity. Use this tool when reviewing content for SEO optimization, assessing academic citation readiness, or ensuring adherence to modern search engine and AI best practices.

Perform a comprehensive, deep-dive audit on a single URL, covering all critical aspects of Search Engine Optimization. Analysis includes on-page elements (title, headings, meta tags), content quality (readability, E-E-A-T), technical structure (schema, canonical, OG tags), image optimization, and core web vitals potential issues. Ideal for SEO audits and content quality checks.

A comprehensive tool for planning and auditing programmatic SEO pages generated at scale from structured data sources (CSV, JSON, APIs). It guides best practices for designing templates, defining scalable URL systems, establishing internal linking strategies (Hub/Spoke), and implementing robust quality gates. Use this when ensuring content uniqueness, preventing thin content penalties, and mitigating risks associated with large-scale, data-driven content generation.

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.

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 tool provides comprehensive observability for enterprise search systems (Glean). It tracks critical metrics such as search latency (p95), zero-result query rates, indexing throughput, and stale content ratios. By monitoring connector sync status and detecting indexing degradation, it allows teams to proactively maintain search relevance and ensure sub-second response times, preventing silent data quality decay.

This skill provides integration with Grammarly's Writing Score API, enabling applications to automatically score documents. It evaluates writing quality across four dimensions: engagement, correctness, clarity, and tone. Use this when building content quality assurance features, implementing quality gates, or providing detailed, multi-dimensional feedback on written content.

Utilizes Grammarly's advanced APIs to conduct comprehensive content auditing. This skill detects the likelihood of AI-generated content and checks the provided text against vast databases for plagiarism. It provides a combined score assessing overall writing quality, clarity, and academic integrity, making it essential for professional, academic, and published content review.