Skill UI

This tool reviews user interface (UI) code files to ensure compliance with established Web Interface Guidelines and best practices. Use it when auditing design, checking accessibility, or performing general code reviews to meet industry standards and improve overall product quality. It fetches the latest rules and outputs detailed findings.

This guide outlines a rigorous, technical framework for receiving and responding to code review feedback. It emphasizes that code review is a technical assessment, not an emotional exchange. Users learn how to verify assumptions, ask clarifying questions, professionally refute incorrect suggestions, and implement changes iteratively, ensuring code quality and architectural integrity.

This guide outlines a systematic workflow for requesting code reviews, crucial for validating completed tasks, implementing major features, or preparing for merge. It emphasizes reviewing early and often, ensuring reviewers focus on the tangible work product rather than the development thought process. Learn how to use specific Git SHAs and structured templates to submit comprehensive feedback requests.

This technique allows users to locate game developers or projects indirectly by searching for highly distinctive biographical details. Instead of relying on game databases, it leverages unique phrases, historical events, or personal lifestyle details found in interviews, blogs, or conference talks. It is invaluable when the developer's identity is obscured, requiring deep research using exact-match queries on obscure information.

This specialized coach provides comprehensive guidance for finance professionals, covering diverse fields such as investment banking, private equity, asset management, and fintech. It teaches core technical skills (DCF, LBO, 3-statement modeling) and prepares users for rigorous industry recruiting, including case studies and technical interviews. It addresses both Chinese and global financial markets, helping users strategically navigate career barriers and build professional expertise.

A comprehensive mentor for graduate students and early-career researchers, guiding the entire research lifecycle. This skill covers formulating rigorous research questions, designing studies (quantitative, qualitative, mixed-methods), conducting literature reviews, analyzing data, and writing publishable papers. It emphasizes methodological rigor, critical thinking, and ethical considerations.

A powerful tool for scientific literature review and evidence synthesis. This skill searches a curated database of full-text scientific papers, going beyond traditional abstracts. It extracts and returns highly structured, quantitative data, including methodologies, quantitative results, sample sizes, quality scores, and 25+ metadata fields per paper, making it ideal for meta-analyses and systematic reviews.

This tool opens the dedicated Context Mode Insight dashboard in your default browser. Insight serves as the central analytics layer for AI-assisted engineering teams, providing crucial metrics such as per-engineer productive rates, identifying retry waste, detecting blockers, and offering role-narrowed performance views. It is designed to be the single source of truth for comprehensive team performance monitoring and sign-in details.

An autonomous research agent that plans complex investigations using Directed Acyclic Graphs (DAGs). It executes sub-questions in parallel, performs gap analysis, and iteratively refines findings before synthesizing a comprehensive, structured report. Ideal for deep market analysis, academic literature reviews, or complex problem-solving requiring multiple data sources.

A systematic framework designed for conducting rigorous peer reviews of scientific manuscripts and grant proposals. It provides a structured, checklist-based evaluation covering methodology rigor, statistical validity, reporting compliance (e.g., CONSORT, STROBE), and assesses all sections from abstract to results. Ideal for academic publishing, research quality assessment, and providing detailed, constructive feedback.

Utilize the ScholarEval framework for comprehensive and structured evaluation of academic works, including research papers, proposals, and literature reviews. Assess quality across critical dimensions like problem formulation, methodology rigor, data analysis, and scholarly writing. Provides both quantitative scoring and actionable feedback to enhance publication readiness.

This skill provides a systematic framework for evaluating the rigor of scientific claims, research methodology, and evidence quality. It guides users through assessing experimental design validity, identifying various types of biases (e.g., selection, cognitive), and applying established grading frameworks like GRADE or Cochrane Risk of Bias. Ideal for systematic reviews, peer review, and critical analysis of scientific literature.