Skill UI

A comprehensive resource for academics targeting the South China Journal of Economics. It provides deep insight into the journal's scope, preferred topics (e.g., Greater Bay Area, open economy, digital economy), rigorous submission standards (anonymous review, fee-free), and structural requirements. Use this guide to evaluate manuscript fit, optimize framing, and reduce the risk of desk rejection before official submission.

This guide clarifies the role of computation in theoretical computer science submissions, particularly for venues that prioritize theorems over empirical data. It distinguishes between legitimate forms of evidence—such as certified proof steps, constructive object discoveries, and illustrative examples—and inappropriate performance benchmarking. It helps researchers structure their work to align with theorem-based research, ensuring computational elements enhance the core theoretical contribution.

A specialized guide for researchers targeting the journal Taxation Research. It helps users vet their manuscripts for alignment with the journal's scope, structure, and academic expectations. The skill covers core themes such as tax reform, digital taxation, and international tax, while providing detailed advice on abstract writing, citation styles, methodology strength, and avoiding common rejection pitfalls.

A comprehensive guide for researchers on assessing the suitability of digital health, AI/ML, or health informatics manuscripts for The Lancet Digital Health. It outlines the journal's strict standards for clinical rigor, external validation, reporting guidelines (TRIPOD, CONSORT-AI), and evidence required for publication.

This skill establishes the root directory for a collaborative workshop, serving as a centralized project hub. It manages two distinct paths: using an existing local directory (Path A), or initializing a new private GitHub repository (Path B). It scaffolds the necessary structure—including `desks/`, `bench/`, and `CAIRN.md`—while strictly preserving existing work and preventing repository nesting. Ideal for standardizing project setup and maintaining collaboration standards.

A comprehensive guide detailing the workflow for converting an accepted academic manuscript into its final, archival format for major digital libraries (e.g., ACM Digital Library). It covers critical steps including completing e-rights forms, de-anonymizing content, verifying CCS concepts and keywords, managing metadata, and troubleshooting common production pitfalls to ensure successful publication.

This workflow performs a comprehensive review against the Azure Well-Architected Framework (WAF) using your existing Infrastructure as Code (IaC) and deployed resources. It systematically checks the five pillars—Reliability, Security, Cost Optimization, Operational Excellence, and Performance Efficiency—identifying architectural risks, drift, and compliance gaps. Findings are automatically logged and converted into actionable GitHub issues for streamlined remediation.

Scans your local machine's Git history to locate abandoned or unfinished side projects. It performs a deep 'autopsy' on these repositories, determining their causes of death (e.g., deployment fear, killed by newer ideas) and identifying personal developmental patterns. The tool then surfaces the most promising candidate for resurrection, helping you finally ship it.

Exa MCP provides advanced neural search capabilities across the web, specialized code repositories (like GitHub), and corporate/personnel databases. Use it for deep background research, finding the latest news, debugging complex code patterns, or conducting thorough market and competitor analysis.

This tool restores project context, crucial after a session clear. It comprehensively analyzes Git history, summarizing recent commits, tracking uncommitted changes, scanning for outstanding TODOs/FIXMEs, and verifying the current project structure. It helps developers quickly re-establish the full working context to resume work efficiently.

Automates the entire Continuous Integration (CI) workflow, crucial before opening a Pull Request (PR). It systematically runs local unit tests for multiple languages (Python, Node, Rust), performs type checking, pushes the current branch to the remote repository, and finally provides the direct URL and status check for the CI platform (GitHub Actions/GitLab). This single command replaces multiple manual steps.

This script automates the Git push process, ensuring safety checks (e.g., preventing direct pushes to main branches) and verifying uncommitted changes. Upon successful push, it dynamically generates and displays direct tracking links for CI pipelines on major platforms like GitLab and GitHub Actions, providing immediate status updates for development teams.