Skill UI

A comprehensive, minimal landing page template designed for product pre-launch or early access sign-ups. It features crucial elements like email capture forms, brand branding, hero sections, and sophisticated decorative overlays (meshes, noise). Perfect for maximizing early interest and lead generation.

A comprehensive guide derived from C++ Core Guidelines, enforcing modern, safe, and idiomatic practices for C++17, C++20, and C++23. It emphasizes crucial principles like RAII, type safety, immutability, and proper resource ownership using smart pointers. Use this when writing new features, reviewing existing code, or making architectural decisions to ensure code quality and consistency.

This skill provides comprehensive operational controls for long-lived, cloud-hosted agent workloads. It manages the entire lifecycle—from deployment and scaling to observability and security. Features include detailed monitoring (logs, metrics, traces), safety controls (kill switches, least privilege), and robust change management processes (rollout, rollback, auditing). Ideal for mission-critical microservices and background agents.

This guide details integrating FoundationModels for running Large Language Models (LLMs) directly on the device (iOS 26). It covers advanced patterns including text generation, extracting structured data using @Generable, implementing custom tool calling for domain logic, and streaming responses for real-time UI updates. Key features emphasize strong privacy and offline capability, ensuring no data leaves the device.

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 guide to building robust, maintainable, and idiomatic Perl applications using modern features (Perl 5.36+). This resource covers best practices for object-oriented programming (Moo/Moose), advanced error handling (Try::Tiny), context sensitivity, complex regex usage, and efficient module design.

A comprehensive guide to writing robust, efficient, and maintainable Python applications. Covers core principles like readability, explicit coding, and EAFP (Easier to Ask Forgiveness than Permission), advanced features like modern type hinting, context managers, and sophisticated exception handling techniques.

Master professional Python testing practices using the pytest framework. This guide covers Test-Driven Development (TDD) methodology, advanced features like fixtures (with different scopes), parametrization, assertion techniques, and achieving high code coverage, ensuring robust and maintainable software.

A comprehensive guide covering best practices for creating videos using Remotion and React. Learn how to incorporate advanced features such as 3D rendering (Three.js), complex animations, audio synchronization, data charting, subtitles, and sophisticated scene transitions. This skill covers 29 domain-specific rules for professional video pipelines.

This tool executes the foundational SPARC Specification Phase (Phase 1) for new features or projects. It guides the user through systematically gathering comprehensive requirements, including functional/non-functional needs, defining concrete acceptance criteria (Given/When/Then), identifying technical constraints, and mapping edge cases. It creates a robust, formalized specification document that serves as the blueprint for all subsequent design and development phases.

This skill calculates model interpretability for algorithmic trading signals using PageRank. It constructs a feature-contribution graph from an LSTM or Transformer signal and executes a single-entry PageRank calculation. The result identifies the top-K features that most significantly drove the prediction, providing a "regulator-grade" audit trail essential for compliance with regulations like the EU AI Act.