Skill UI

A powerful tool that converts complex Unified Modeling Language (UML) diagrams—such as Sequence, Class, Activity, and State diagrams—into plain text ASCII art. This is crucial for documentation in environments that do not support image embedding, such as terminal sessions, README files, or Git commit messages. Supports both standard ASCII and enhanced Unicode ASCII formats for better visual fidelity.

This skill transforms a raw Python script into a polished, beginner-friendly project package. It automatically refactors the code to adhere to PEP 8 standards, adds comprehensive, instructional comments explaining the 'why' behind the logic, and generates a complete, professional `README.md` file. The resulting project is immediately ready for use in educational settings, portfolios, or for onboarding new developers.

Converts text-based documentation into structured Markdown by following explicit instructions, documented options, or reference files, supporting header levels, patterns, platforms, and cleanup steps for polished technical documents.

Explains Fabric Lakehouse storage, data organization, security, shortcuts, and optimization practices so you can design, build, and monitor Lakehouse solutions leveraging Microsoft Fabric best practices.

This script provides a lightweight, standalone Python integration for Google Sheets, offering full read and write access without needing a dedicated server. Users can retrieve spreadsheet data in multiple formats (plain text, CSV, JSON), extract specific ranges, find sheets via search queries, and perform advanced write operations like updating, appending, or clearing cell values. It is highly suitable for automating data reporting, extraction, and workflow integrations involving Google Workspace.

Provides an expert Spring Boot 4 testing guide that explains the test pyramid, slice annotations, AssertJ-centric assertions, MockMvcTester, RestTestClient, Testcontainers, and practical coverage goals.

This skill systematically reviews test code to identify and correct common anti-patterns. It detects issues such as flaky tests, overly mocked dependencies (over-mocking), brittle assertions, excessive test size (The Giant), and structural dependencies. It explains the flaw, provides best practices, and suggests refactored, reliable implementations, helping maintain high test quality and stability.

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.

This guide provides comprehensive troubleshooting for common Attio REST API errors, detailing specific HTTP status codes (e.g., 400, 401, 429, 422). It explains the required error response format, common causes (like invalid scopes or rate limits), and actionable, proven fixes using code examples and best practices.

Provides a comprehensive guide for managing Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. It covers direct query execution, robust schema management, safe schema evolution, multi-tenant isolation patterns, and IAM authentication. Use cases include database development, complex migrations (e.g., MySQL to DSQL), and optimizing query performance using detailed plan explainability tools.

A comprehensive guide for working with Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. This skill covers full lifecycle development, including schema management, data migration (e.g., MySQL to DSQL), multi-tenant patterns, IAM authentication, and advanced query plan explainability. Essential for building robust, scalable applications.

A comprehensive guide for developing and managing applications using Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. This skill covers core capabilities including direct query execution, robust schema management, safe data migration from MySQL, multi-tenant architectural patterns, IAM-based authentication, and detailed query plan explainability for performance tuning. Essential for developers handling complex database evolution.