Skill UI

Provides automated guidance for designing and implementing cron job schedulers in backend projects, covering best practices, production-ready code, and validation for node.js, Python, Go, databases, and microservices patterns.

A comprehensive guide for integrating and managing VS Code extensions within the Cursor IDE environment. This resource details the transition from the Microsoft Marketplace to the Open VSX Registry, covering installation methods (in-app, VSIX, CLI), conflict resolution with advanced AI features (e.g., Copilot, TabNine), and best practices for ensuring optimal performance and recommended extension stacks for various languages like Python, JavaScript, and Go.

Guides data engineering patterns for ETL pipelines, Spark analytics, and quality checks, showcasing Python and SQL snippets to extract, transform, load, validate, and model sales data in modern warehouses.

Automates database schema design guidance for backend projects, activating whenever you ask about schema patterns, best practices, or implementation in node.js, Python, Go, microservices, caching, or messaging contexts.

A comprehensive guide detailing the setup process for Databricks CLI v2 and Python SDK. It covers essential steps for connecting to various Databricks workspaces, including configuring Personal Access Tokens (PAT), interactive OAuth U2M flows, and secure OAuth M2M service principals for CI/CD pipelines. Essential for developers integrating Databricks into their projects.

A comprehensive guide to production-ready patterns for the Databricks Python SDK. This skill covers essential best practices including singleton client initialization, structured error handling with typed exceptions, context-managed cluster lifecycle control (ensuring cleanup), and implementing type-safe job definitions. It is essential for building robust, maintainable, and idiomatic integrations with the Databricks platform.

A comprehensive guide detailing best practices for building reliable, fault-tolerant Python applications utilizing DBOS durable workflows. This resource is essential when integrating DBOS into existing Python codebases, defining complex workflows and steps, managing concurrency via queues, or implementing robust workflow communication patterns.

Collects comprehensive, sanitized debug evidence for Deepgram support and troubleshooting. This bundle gathers detailed system environment information (Node.js, Python), performs live API connectivity tests, analyzes audio file metadata using ffprobe, and logs request/response data. Essential for preparing detailed support tickets and reproducing bugs related to Deepgram integration.

This guide provides minimal working examples for Deepgram speech-to-text transcription. It demonstrates how to transcribe audio from a URL or a local file using both TypeScript and Python. Users can learn basic API patterns, implement advanced features like diarization (speaker identification), and compare various model options (e.g., nova-3, nova-2). Ideal for initial integration and testing.

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.

A powerful tool for comprehensive, offline dependency auditing across 8+ programming ecosystems (e.g., Node, Python, Go, Rust). It identifies critical CVE vulnerabilities, license conflicts, and calculates safe upgrade paths, making it essential for pre-release security checks, legal compliance reviews, and major version migrations.

Automates devcontainer creation with Claude Code plus language-specific tooling for Python, Node/TypeScript, Rust, and Go, layering templates, extensions, and post-create commands so teams can spin up isolated, persistent workspaces quickly.