Skill UI

A structured workflow designed to prevent 'reinventing the wheel.' Before writing custom code, this skill guides the user through analyzing needs, conducting parallel searches across multiple channels (npm, PyPI, GitHub, MCP), evaluating candidate solutions based on maintainability and community support, and making a decision (Adopt, Extend, or Custom Build). It ensures that solutions leverage existing, proven libraries and patterns.

Skill Scout is a crucial pre-creation workflow designed to prevent the duplication of effort. Before building a new skill, it systematically searches local, marketplace, GitHub, and web sources. It not only finds potential matches but also rigorously vets them for security, maintenance status, and relevance, providing the user with clear options: Use Existing, Fork/Extend, or Create New.

This skill acts as an expert guide for creating comprehensive, implementation-ready design system documentation. It structures guidelines by defining foundational tokens (color, typography, spacing), detailing component anatomy, interaction states, and adhering to strict accessibility standards (WCAG 2.2 AA). Use it to ensure your design standards are consistent, technically sound, and actionable for engineering and design teams.

This expert skill generates comprehensive, implementation-ready documentation for the Stitch design system. It covers style foundations, semantic tokens, component anatomy, accessibility requirements (WCAG 2.2 AA), and content standards. Ideal for ensuring visual consistency and creating robust, enterprise-grade user experiences across data-driven applications and AI workflows.

Provides a structured workflow for systematically accessing and analyzing official intellectual property data from the USPTO. This skill covers patent search (PatentSearch API), trademark status checks (TSDR), ownership transfer tracking, and building reproducible IP landscape logs. It is designed for data collection and record verification, emphasizing the use of official APIs and rigorous logging practices. (Warning: Not for legal advice.)

This example demonstrates unsafe or malicious review data inputs, specifically designed for calibration and security testing. It simulates prompt injection attacks and must only be used in controlled environments to validate secure data processing and system robustness.

This skill is designed to review Chinese skill documentation to ensure it meets publishing standards. It systematically checks the clarity of descriptions and the executability of process steps, providing structured feedback in Chinese while maintaining necessary machine enumeration values for technical integrity.