Skill UI

This skill unlocks advanced multi-step code generation and architectural refactoring capabilities using autonomous agents. It supports parallel agent workflows, complex multi-file migrations, and multi-codebase orchestration by autonomously calling tools (Read, Write, Bash) in controlled, checkpointed cycles, drastically improving large-scale development efficiency.

A comprehensive guide to mastering AI-powered coding assistance within the IDE. Learn to use the chat panel for conversational debugging and architectural discussion, and utilize inline editing for surgical code refactoring. Features advanced context referencing using @-mentions (e.g., @Files, @Codebase) to improve code understanding and generation accuracy.

A powerful AI tool designed for complex, coordinated programming tasks. It enables developers to generate, refactor, and scaffold entire features across multiple files (e.g., schema, API routes, service layers, tests) while maintaining consistency with existing codebase patterns. It supports agent mode for autonomous, multi-step changes and allows systematic migration and review of all affected files via detailed diffs.

A comprehensive guide to optimizing context window usage within AI coding environments like Cursor. Learn how to strategically use @-mentions, manage context pills, and leverage different context sources (codebase, documentation, web) to prevent context overflow and ensure the AI generates highly accurate, relevant, and context-aware code suggestions and answers for complex development tasks.

A comprehensive guide to structuring effective custom prompts for AI coding assistants like Cursor. Learn the four components of prompt anatomy (Context, Task, Constraints, Format), and utilize reusable templates for complex tasks such as feature implementation, bug fixing, code review, and test generation. Master advanced techniques like Chain of Thought and Few-Shot examples to ensure high-quality, consistent code output.

This bundle provides a comprehensive framework for diagnosing and fixing common issues when AI code generation is incorrect within Cursor. It systematically covers the root causes of poor suggestions, including context mismanagement (missing, wrong, or overflowing context), model hallucinations, and ambiguous prompting. Use this guide to improve the accuracy and reliability of AI-assisted coding workflows.

This tool integrates advanced AI capabilities into the entire Git lifecycle within the IDE. It assists developers by automatically generating standardized commit messages from staged diffs, providing deep code review using the @Git context (checking for vulnerabilities, missing handling), and offering systematic guidance for resolving complex merge conflicts. It streamlines version control and elevates code quality.

This is a hands-on walkthrough demonstrating the four core AI features of the Cursor IDE: Tab Completion, Chat, Inline Edit, and Composer. Users learn how to leverage AI for coding tasks, debugging, generating boilerplate code, and performing multi-file refactoring within a structured project environment. It's an essential guide for developers adopting AI-assisted coding workflows.

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 debugging bundle designed to collect all necessary evidence for Customer.io support tickets. It performs API connectivity diagnostics (Track/App), validates user profiles, captures environment details (Node.js, SDK versions), and generates a structured report. Ideal for investigating delivery failures or complex integration issues.

A comprehensive, expert-level skill for designing, analyzing, and optimizing robust database schemas. It covers normalization, index tuning, choosing between SQL/NoSQL, and implementing zero-downtime data migrations. Provides systematic workflows for schema analysis, performance modeling, and advanced SQL pattern generation.

This skill automates the creation of comprehensive documentation for relational databases (PostgreSQL/MySQL). By introspecting live schemas, it extracts detailed metadata including table structures, column descriptions, primary/foreign key relationships, indexes, views, and stored procedures. The output provides a data dictionary, entity-relationship map, and schema statistics, crucial for knowledge transfer and database lifecycle management.