Skill UI

Behavioral rules for LLMs writing or reviewing code, emphasizing caution, simplicity, surgical edits, and goal-driven execution to avoid common mistakes during implementation tasks, bug fixes, or refactors.

Analyzes namespaces to spot root-level orphaned classes, highlights hierarchy violations, and produces flattening or refactoring plans that keep components at leaf-level directories.

This skill guides the execution of development tasks defined in a structured implementation plan, strictly following the Test-Driven Development (TDD) workflow. It manages the entire development lifecycle, including pre-flight checks, context loading, task identification, writing failing tests, implementing minimal code, refactoring, committing changes, and performing phase-wise verification. Ideal for managing complex, structured software development projects.

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.

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.

A comprehensive guide to mastering Cursor IDE's keyboard shortcuts. This resource covers dedicated AI features (such as Inline Editing and Chat interaction) alongside essential standard IDE commands (navigation, refactoring, etc.). Learn how to utilize, customize, and manage keybindings via the UI or JSON for maximum development efficiency.

A comprehensive guide for safely upgrading and migrating the Customer.io Node SDK. It details the necessary steps for handling major version changes, such as transitioning from the legacy CustomerIO class to the modern TrackClient and APIClient pattern. Use this skill when refactoring old code, adapting to breaking API changes, or ensuring compatibility with the latest SDK best practices.

This skill provides a comprehensive and isolated setup for managing Deepgram API integrations across different deployment stages (Development, Staging, Production). It includes typed configuration management, a client factory pattern, and Docker Compose profiles, ensuring that each environment uses specific credentials, models, and feature settings (like diarization or PII redaction) without conflict. Ideal for robust, multi-stage application deployment.

Provides production-ready coding patterns for integrating Deepgram using TypeScript and Python. This guide covers essential best practices, including implementing singleton client management, performing text-to-speech synthesis with Aura, and setting up advanced audio intelligence pipelines (e.g., summarization, topic detection, sentiment analysis). Use this when establishing robust Deepgram integration standards, refactoring existing SDK usage, or migrating to newer SDK versions.

Provides Django testing strategies combining pytest-django, factory_boy, DRF helpers, mocking, and coverage so teams can adopt TDD workflows for models, views, serializers, and APIs.