Skill UI

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.

Master the art of developing robust and scalable Python applications that interface with Microsoft Dataverse. This skill covers implementing enterprise-grade best practices, including comprehensive error handling using DataverseError hierarchy, advanced retry logic with exponential backoff, and optimizing API calls using OData standards (filtering, selecting, and expanding). It ensures code is clean, maintainable, and production-ready.

Generates Power Platform custom connectors with MCP integration for Copilot Studio, covering schema generation, JSON-RPC scripts, validation, troubleshooting, OAuth hardening, and CLI guidance for paconn/pac workflows.

This skill provides advanced architectural guidelines for generating premium, award-level web experiences. It guides code generation beyond basic HTML/CSS, focusing on creating immersive digital environments. Key areas include sophisticated motion design (scroll-driven narratives, micro-interactions), establishing strong visual identities (e.g., Brutalism, Glassmorphism), and enforcing strict performance best practices like hardware acceleration and accessibility compliance.

A comprehensive tool for detecting, validating, and generating Schema.org structured data. It primarily focuses on the JSON-LD format, which is preferred for modern SEO best practices and enabling rich results. Use this when optimizing content markup, checking for validation errors, or generating structured snippets for articles, businesses, or products.

This skill guides the implementation of essential user feedback states—Loading (Skeleton), Empty (Zero Data), Error, and Success—for data-dependent components or entire pages. It ensures a robust and polished user experience by providing structured, best-practice patterns for handling various data scenarios, preventing visual gaps or dead ends in the UI flow.

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.

RDKit is a comprehensive cheminformatics library providing robust Python APIs for molecular structure manipulation and analysis. It supports tasks ranging from molecular I/O (SMILES, SDF) and calculating physical descriptors (MW, LogP) to advanced substructure searching, 3D coordinate generation, and chemical reaction modeling. It is an essential toolkit for drug discovery, computational chemistry, and academic cheminformatics research.

Guide to building and troubleshooting TorchDrug 0.2.1 workflows for molecular graphs, property prediction, pretraining, generation, retrosynthesis, protein learning, and knowledge graph reasoning.

The Hugging Face Transformers library is a comprehensive toolkit providing access to thousands of pre-trained models across diverse domains including Natural Language Processing (NLP), Computer Vision, Audio, and Multimodal tasks. It enables developers to easily load models, perform high-level inference (e.g., text generation, classification, QA), and fine-tune models on custom datasets using streamlined APIs like Pipelines and the Trainer class. Ideal for building advanced, state-of-the-art AI applications.

This tool automates the complete specification generation process across four core phases: Initialization, Requirements, Design, and Tasks. It supports both interactive (step-by-step approval) and automatic execution modes. After generating the full spec, it performs a final sanity review to ensure coherence and completeness, providing a ready-to-implement blueprint.

This comprehensive guide provides minimal working examples for key Adobe APIs: Firefly AI image generation, PDF content extraction, and Photoshop background removal. It serves as a practical quickstart for developers starting new Adobe integrations, testing API connectivity, or learning basic API calling patterns using TypeScript and Node.js.