Skill UI

This skill teaches you how to handle errors in TypeScript without relying on try/catch blocks. It focuses on using fp-ts Either and TaskEither types to make error handling more predictable and type-safe. Ideal for building APIs, services, and accumulating validation errors. It promotes treating errors as data values rather than exceptions, ensuring cleaner and more maintainable code.

Guidance for selecting and using Apple Human Interface Guidelines (HIG) selection and input controls, including toggles, segmented controls, sliders, pickers, steppers, text fields, combo boxes, token fields, gauges, and rating indicators. Helps developers choose the right control for their data type, understand state management, validation, and accessibility.

Train object detection, image classification, and SAM/SAM2 segmentation models locally or on Hugging Face Jobs with dataset validation and Hub saving.

Automate binary reverse engineering with IDA Pro using MCP. Includes decompilation, disassembly, data-flow tracking, and cross-references. Features PowerShell scripts for server management and file handling to bypass schema validation and permission issues. Supports PE/ELF/Mach-O targets.

This skill enforces a rigorous data validation protocol by establishing hard boundaries at every point data enters the system (API requests, user input, environment variables, webhooks, etc.). It mandates a four-phase process: detection, trust classification, mandatory filtering (schema validation, sanitization, type checking), and final verification. This prevents untrusted data from reaching core business logic, mitigating risks like SQL injection and XSS.

Secure LLM-powered applications against prompt injection, data leakage, and abuse using input validation, output controls, and tenant isolation. Implements OWASP LLM Top 10 mitigations with Python and Node.js examples.

End-to-end MLOps pipeline orchestration guidance covering data preparation, model training, validation, deployment, monitoring, and workflow automation best practices.

This skill specializes in secure mobile application development, focusing on input validation, WebView security, and mobile-specific security patterns. It covers secure data storage, authentication implementation, and platform-specific vulnerabilities for iOS and Android. Ideal for building security-first mobile apps that protect sensitive data and resist common attack vectors like injection attacks and man-in-the-middle threats.

Generates SQL validation notebooks for dbt PR changes with before/after comparison queries. Supports GitHub PR URLs and local repositories. Creates interactive notebooks for database validation across Snowflake, BigQuery, Redshift, and Athena. Includes schema inference from dbt_project.yml and model configs.

This skill enables users to discover and access NEXRAD radar data for specific sites, times, and products. It supports retrieving Level II archive volumes, real-time chunks, and Level III sources with metadata validation. It helps select reflectivity, velocity, and other radar moments from AWS S3 buckets while ensuring data integrity.

PydanticAI is a robust Python framework that integrates Pydantic's type-checking and validation capabilities into Large Language Models (LLMs). It allows developers to build production-ready AI agents that guarantee structured, validated outputs, moving beyond simple raw strings. Key features include supported tool calling, dependency injection for testability, and multi-model compatibility across major providers like OpenAI, Anthropic, and Gemini. Use this when reliability and correct data structure are paramount.

An end-to-end workflow for building robust, production-ready Python backend APIs. This guide covers all stages, including project scaffolding, SQLAlchemy database integration, Pydantic validation, implementing JWT/OAuth2 authentication, comprehensive error handling, unit testing, and Docker deployment for modern microservices.