Skill UI

A comprehensive guide for setting up and maintaining Cursor IDE for enterprise and production use. It covers essential best practices including security hardening, defining project-wide coding rules, optimizing codebase indexing, ensuring data privacy compliance, and standardizing team development workflows. Essential for adopting AI coding tools in a professional environment.

A comprehensive reference guide for structuring development projects within the Cursor IDE. It details best practices for directory layout, defining layered rules (covering global conventions, security constraints, and technology-specific patterns like API routes and database access), and optimizing indexing strategies. This ensures maximum AI effectiveness, improves code maintainability, and streamlines the entire development workflow.

Manages and enforces project-specific coding standards and architectural conventions within the Cursor IDE. Developers can define rules using `.mdc` files, specifying required patterns (e.g., TypeScript strict mode, React component structure, API validation). This system guides the AI assistant by providing deep context, ensuring code consistency and adherence to best practices across the entire codebase.

A comprehensive guide for setting up Single Sign-On (SSO) for Cursor IDE using industry standards like SAML 2.0 and OpenID Connect (OIDC). This guide supports major Identity Providers, including Okta, Microsoft Entra ID, and Google Workspace. It covers configuration steps, attribute mapping, SCIM provisioning, and best practices for enterprise-level authentication and user lifecycle management.

Guides creation of Cursor-specific subagents with isolated contexts, structured prompts, and frontmatter so multi-step workflows, verifiers, or specialists follow Cursor’s directories and delegation rules.

Master Cursor's AI-powered Tab completion system, generating instant, context-aware 'ghost text' suggestions. This tool predicts the next code lines based on the current file, open tabs, and even comments, allowing developers to accept or modify suggestions with minimal effort. It is designed to significantly boost coding speed and maintain coding consistency.

A comprehensive guide for administrators and teams on setting up Cursor for enterprise use. It covers organizational plan selection (Pro, Business, Enterprise), advanced features like SSO, SCIM provisioning, and Privacy Mode enforcement. The guide details setting up roles, managing usage analytics, defining shared project rules via Git, and providing a structured onboarding checklist to ensure seamless adoption and secure coding practices across the organization.

A comprehensive guide covering how to upgrade Cursor IDE versions, migrate settings and configurations from VS Code, and reliably transfer your entire development environment between different machines. Includes steps for auto-update, manual installation, and handling breaking changes.

This comprehensive dashboard tracks and analyzes usage metrics for AI coding assistants (Cursor) in enterprise environments. It monitors total requests, model consumption, user adoption rates, and associated costs. Managers can use it to optimize resource quotas, control AI spending, and calculate the Return on Investment (ROI) to justify AI tool adoption.

A comprehensive guide covering advanced patterns for the Linear SDK using TypeScript/JavaScript. Learn how to implement efficient cursor-based pagination, avoid N+1 query problems by batch-loading relations, perform complex filtering, and handle API calls with type-safe error management when integrating with the Linear GraphQL API.

This skill provides advanced techniques for optimizing throughput and reducing latency when interacting with the Lokalise API. Learn to implement cursor-based pagination for massive key sets, establish robust local caching strategies using project activity timestamps, and utilize efficient batch operations (up to 500 items) for creating or updating keys. Essential for building scalable, high-performance translation pipelines.

This guide provides production-grade coding patterns for integrating Lokalise into TypeScript and Node.js applications. It covers crucial best practices such as client singleton implementation, robust cursor-based pagination for large datasets, structured error handling with retry logic, and efficient batch operations. Implementing these patterns ensures reliable, scalable, and maintainable API usage.