Skill UI

This skill ensures a comprehensive understanding of a project's technical history by reading every Architecture Decision Record (ADR) in the designated folder. It is crucial to use this when summarizing architectural context, making major changes, or evaluating project decisions, guaranteeing nothing is missed.

This skill guides the design, implementation, and auditing of inclusive digital products based on WCAG 2.2 standards. It covers the POUR principles and provides technical guidance for generating semantic ARIA (Web) and native accessibility traits (iOS/Android). Use it when defining UI components, auditing compliance gaps, or ensuring robust keyboard navigation and focus management.

This skill guides users through Phases 2 (Pseudocode Design) and 3 (Architecture Design) of the SPARC methodology. It translates high-level specifications into detailed technical blueprints, covering algorithm pseudocode, module boundaries, API contracts (using DDD patterns), and infrastructure planning, ensuring a robust plan before writing production code.

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 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 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.

Designs an end-to-end, cross-platform retargeting playbook. This tool maps user behavior across the entire conversion funnel, segmenting audiences by stage (e.g., cart abandoners, viewers). It provides detailed guidance on creative sequencing, frequency capping, cross-platform coordination (Meta, Google, TikTok), budget allocation, and technical tracking setup, ensuring a coherent and optimized customer journey.

This guide provides a comprehensive, advanced strategy for academic researchers writing microeconometric papers for top-tier journals (e.g., AEJ: Applied). It teaches authors how to anticipate sophisticated, technical objections from expert referees (such as issues with causal inference design, selection bias, or parallel trends). The focus is on pre-empting these objections by integrating solutions directly into the manuscript text, rather than waiting for a formal revision letter.

A comprehensive pre-submission strategy tool designed for authors submitting to top macroeconomics journals, such as AEJ: Macro. It helps authors anticipate and structure defenses against predictable, highly technical objections (e.g., identification flaws, robustness gaps, lack of breadth) raised by expert referees and co-editors. Use this guide to assess desk-reject risk, plan necessary robustness checks, and pre-emptively strengthen the manuscript before formal submission.

A comprehensive preflight checklist designed for authors submitting high-level academic manuscripts (e.g., AMS-LaTeX articles). It guides users through verifying technical formatting, mathematical rigor, reference consistency, and logistical requirements before final portal submission. It ensures the manuscript is ready for peer review, focusing on structure and format, not scientific merit.

This guide outlines best practices for designing and executing Computer Aided Verification (CAV) empirical evaluations. It emphasizes ensuring evidence matches claims by using standard, pinned benchmark sets, selecting fair baselines, respecting equal resource limits, and employing rigorous reporting methods like cactus and scatter plots to establish technical soundness and performance.

A detailed guide for scrutinizing statistical inference in high-level econometric manuscripts, designed to withstand rigorous technical peer review. It covers critical areas such as selecting appropriate clustering levels, handling weak instrumental variables (IV), correcting for multiple hypothesis testing, and ensuring accurate standard error reporting for panel data and causal inference models.