Skill UI

Structured manuscript and grant review guidance that walks reviewers through methodology, statistics, reporting compliance, and constructive feedback for rigorous scientific evaluation across disciplines.

This skill runs the ScholarEval framework to score academic submissions across problem setting, methodology, data, analysis, writing, and references, providing structured strengths/weaknesses, numeric ratings, and guidance for visualizing the evaluation.

Structured system that runs multi-branch “what if” analyses to map possibility spaces, stress-test strategic options, and surface triggers so users can prepare confident responses before committing resources.

A comprehensive set of rules and constraints designed to optimize AI interaction in technical domains. It guides the agent on intelligent input filtering (handling logs, Git, codebases), resolving ambiguity, and generating surgically precise, structured outputs. Ideal for complex debugging, refactoring, and long-session development tasks.

This skill acts as a comprehensive Music Learning Coach, guiding users through the full spectrum of music education. It covers fundamental music theory (scales, harmony), structured instrument practice routines, advanced ear training techniques, performance skills, and deep dives into music history. Ideal for beginners and advanced learners looking to build a solid, well-rounded understanding and practical ability in music.

Access and query 78 public databases covering diverse fields including biomedical, physical sciences, earth science, and economics. This skill identifies the relevant database(s) for user queries (e.g., genes, compounds, patents, climate data, financial indicators), executes structured REST API calls, and returns raw JSON results, providing a comprehensive data retrieval pipeline.

This skill generates comprehensive and structured requirements documents for a new specification. It systematically aggregates context from project files, business rules, and technical constraints, ensuring all generated requirements focus on user-observable behavior (WHAT) rather than implementation details (HOW). It follows established standards like EARS format and includes a rigorous review gate to ensure scope clarity and completeness.

This expert acts as a Design Systems Lead and Prompt Engineer for creating high-fidelity, consistent UI designs. It transforms vague ideas into structured specifications by enhancing prompts with professional UI/UX terminology, synthesizing design system source files, and managing multi-step generation and editing workflows using the Stitch MCP.

Comprehensive runbook for managing Adobe API integration outages, covering Firefly, PDF Services, and IMS authentication failures. Provides structured procedures for initial triage, determining severity (P1-P4), executing recovery steps (Auth/Rate Limit), implementing fallback modes, and documenting post-incident reports and communication.

This guide provides a reference architecture for automating the design-to-code workflow. It outlines the complete pipeline—from Figma design input to structured React/Vue output—detailing components like Figma API integration, code generation, and crucial post-processing steps (token mapping, normalization). Ideal for establishing scalable design systems and managing large-scale design handoffs in a professional environment.

A comprehensive diagnostic reference for resolving common technical failures encountered when running web scraping and automation tasks on the Apify platform. Covers issues such as Actor run failures, API rate limits (429), authentication errors (401), anti-bot blocks, and memory allocation issues, providing structured fixes and best practices for robust scraping pipelines.

This utility provides a structured way to manage and separate notes across multiple accounts and environments within Apple Notes. By utilizing distinct accounts (e.g., iCloud for Production, 'On My Mac' for Development), users can ensure absolute data isolation between development, staging, and live production data. It is crucial for maintaining clean separation in complex development workflows and QA testing scenarios.