Skill UI

This skill fetches the latest, live documentation and code examples for specific libraries and frameworks (e.g., Next.js, React, Prisma). Instead of relying on static or outdated training data, it utilizes the Context7 MCP to provide accurate, up-to-date answers for setup questions, API references, and code generation based on current best practices.

This guide provides comprehensive, structured error handling patterns for modern applications using TypeScript, Python, and general architectural principles. It covers essential concepts like typed custom errors, Result patterns, API error transformers, and React Error Boundaries. Learn how to implement fail-fast mechanisms, differentiate user-facing messages from developer logs, and ensure system resilience against unexpected failures.

This guide details the Hexagonal Architecture (Ports and Adapters) pattern, a robust method for decoupling core business logic from external infrastructure concerns. It teaches how to structure applications to make the domain model independent of databases, UI frameworks, or message queues. Implementing this pattern drastically improves testability, maintainability, and the ability to swap out external services without rewriting business rules.

This skill helps transform vague product or engineering ideas into structured, verifiable acceptance criteria (AC). It is crucial for high-impact changes involving security, data migration, or external APIs. By inspecting existing context and asking minimal, targeted questions, it produces clear, observable criteria, significantly de-risking the development process and ensuring handoff readiness.

Generates professional PNG icon image sets for the Xcode Asset Catalog, supporting both massive open-source collections via Iconify API and native Apple symbols via SF Symbols. Use this tool to streamline the creation, search, and replacement of app icons, ensuring consistency in style, size, and color across your iOS project.

This comprehensive skill provides deep integration with Jira, enabling users to manage the entire issue lifecycle. Features include retrieving ticket details, extracting testable requirements and acceptance criteria, updating issue status (transitions), adding comments, and linking code artifacts (PR/MR). Supports both recommended MCP server approach and direct REST API calls for robust development workflow automation.

A comprehensive guide for integrating transactional email sending into applications using Mailtrap's Email API. It covers critical best practices, including separating development (Sandbox) and production environments, implementing secure Bearer token authentication, and performing essential domain verification (SPF, DKIM, DMARC). Use this when building features like password resets or debugging email delivery pipelines.

A comprehensive, end-to-end methodology designed for software engineers and AI agents to safely and systematically integrate machine learning models into existing non-ML codebases. It guides users through critical phases, including problem framing, data readiness, architectural decoupling (via APIs/services), baseline model implementation, and final MLOps pipeline setup.

This comprehensive API provides a robust solution for automated document workflows. Users can perform format conversions (PDF, DOCX, XLSX, etc.), extract structured data (text, tables), perform OCR on scanned documents, redact sensitive information (PII), add watermarks, and apply digital signatures. Suitable for building automated, secure document processing pipelines.

This tool detects and flags Personally Identifiable Information (PII) across text, code, and configuration files. It is essential to use this before committing code, writing logs, or generating model responses to prevent accidental exposure of sensitive data. It identifies various types of PII, including emails, phone numbers, SSNs, credit card numbers, API keys, and passwords, offering quick checks, detailed scans, and full context-aware analysis.

This skill reviews prediction market, basket, oracle, and trading-agent workflows to ensure compliance, safety, data quality, and privacy. It must be run before any workflow handles user portfolio data, venue authentication, API keys, or trade planning to mitigate execution and regulatory risks across multiple domains.

A comprehensive guide detailing the architectural standards, technology stack, file structure, and coding patterns for building modern, AI-driven full-stack applications. It covers best practices for Next.js, FastAPI, database interaction (Supabase), and structured AI integration (Claude), ensuring consistency and scalability across the development lifecycle.