Skill UI

Generates a complete, compilable xUnit integration test project structure for validating complex database migrations, specifically from Oracle to PostgreSQL, within .NET solutions. This scaffolding includes a transaction-rollback base class and a seed data manager, ensuring a robust environment for writing migration integration tests without requiring test cases. Ideal for setting up testing infrastructure before migration validation.

A universal assistant for conducting deep code reviews across major SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). It rigorously analyzes SQL code for critical vulnerabilities (like SQL injection), performance bottlenecks, maintainability issues, and adherence to industry best practices. Features include security audits, index optimization recommendations, query structure analysis, and schema design validation, ensuring robust and secure database development.

Cross-database SQL performance optimization assistant offering query tuning, indexing strategies, pagination, batch operations, and monitoring guidance for MySQL, PostgreSQL, SQL Server, Oracle, and other relational systems.

Automates Supabase projects by sequencing Composio Rube MCP workflows for database querying, schema inspection, SQL execution, project/org management, storage buckets, edge functions, and health monitoring while always refreshing tool schemas first.

This skill is designed for understanding complex database structures. It allows users to list all available tables, intelligently filter relevant tables based on natural language queries, retrieve detailed schemas (columns, types, primary/foreign keys), and map inter-table relationships. It culminates in generating the M-Schema format, which is essential for accurately preparing the context needed for advanced SQL query generation.

Pymatgen is a comprehensive Python toolkit designed for computational materials science. It enables users to create, analyze, and manipulate complex crystal structures, calculate electronic properties (DOS, band structures), simulate phase transitions, and interact with large material databases like the Materials Project. Ideal for solid-state physics, chemistry, and advanced materials research.

This runbook provides systematic procedures for diagnosing and resolving common automation failures specific to Apple Notes on macOS. It covers critical local issues like app crashes, iCloud sync failures, TCC permission revocations, and database corruption, following a comprehensive detect-diagnose-fix-verify cycle. Essential for maintaining reliable Notes automation workflows.

A comprehensive guide for Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. This skill covers the entire database lifecycle, including schema management, direct query execution, complex data migrations (e.g., MySQL to DSQL), and advanced performance tuning via query plan analysis (EXPLAIN ANALYZE). Essential for secure, multi-tenant application development.

Provides a comprehensive setup guide for running ClickHouse locally using Docker Compose. This includes defining the database schema, seeding mock data, and setting up robust integration tests (using vitest). Ideal for developers building OLAP systems or performing local data analysis to ensure schema and query reliability.

A comprehensive guide to implementing advanced user behavior tracking and real-time data synchronization with Algolia. This guide demonstrates how to use the Insights API to track clicks, conversions, and views, and how to build event-driven pipelines using database change listeners (e.g., Prisma middleware) to keep your Algolia index perfectly synced with your core application data. Essential for deep search analytics and relevance tuning.

A comprehensive, production-ready reference architecture for building robust, scalable transcription services using AssemblyAI. This guide demonstrates best practices for layered system design, covering API endpoints, service logic, client management, and infrastructure integration (webhooks, database). It is ideal for designing new high-throughput speech-to-text applications.

This comprehensive guide provides a production-ready reference architecture for implementing scalable search using Algolia. It details best practices for index design (including multi-index strategies), establishing robust data pipelines from source databases, structuring the service layer (search, indexing, settings), and integrating the frontend for optimal performance.