Skill UI

This guide outlines the comprehensive policy and architecture required for submitting a fully reproducible replication package to The Review of Economics and Statistics (REStat). It details how to structure the repository, including data, master scripts, and the README file, ensuring that every result can be traced and regenerated by other researchers.

This guide details how to assemble a submission-ready replication package for top academic journals, such as The Review of Economic Studies (REStud). It covers the necessary repository structure, mandatory README sections, and coding best practices (e.g., master scripts, relative paths, version pinning) to ensure that the data and code can be fully reproduced and verified by journal editors before publication.

A comprehensive guide for packaging and submitting artifacts for Information Retrieval (IR) conferences (like SIGIR). It details the strict requirements for reproducibility, including mandatory components like TREC-format run files, qrels, and index recipes. The process covers repository structure, anonymization for review, handling data provenance, and ensuring that results can be audited by any reviewer using standard community tooling.

This guide details the critical 'triage protocol' for structuring academic papers for highly constrained venues like SIGIR. It outlines the three-container model (Paper Body, References, Repository) and provides expert advice on prioritizing review-critical evidence, implementing effective content compression techniques, and managing external repository material to ensure submissions meet strict page budgets without sacrificing soundness or review quality. Essential reading for researchers.

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.

This guide outlines the mandatory requirements for authors publishing quantitative or mixed-method research in academic journals. It details the process of creating a complete replication package—including raw data, master scripts, seeds, and extensive README documentation—and depositing it in a trusted data repository (like Dataverse). It ensures scholarly rigor by guaranteeing that published findings are fully reproducible and traceable.

A comprehensive guide for allocating content across academic conference submissions, ensuring critical evidence is visible within strict page limits. It defines rules for triaging material into decisive (body), supporting (appendix/repo), and archival (repository) categories, along with advanced compression tactics for tables and proofs.

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 tool provides a preferred, end-to-end method for modifying code in real-world repositories. It simulates a professional development workflow: cloning the target repository, running changes on a dedicated task branch, and critically, verifying the implementation through an independent red $\to$ green $\to$ regression test loop. It is designed for fixing GitHub issues, implementing new features, or adding functions to existing codebases, ensuring the structural integrity and correctness of the changes.

This tool performs a comprehensive analysis of AI configuration file evolution within a Git repository. It tracks when specific AI configs were first introduced, charts monthly commit velocity related to AI features, highlights key PRs that shaped the development, and synthesizes the project's AI maturity phases. Ideal for mapping AI adoption timelines and assessing technical maturity.

A robust tool for batch cleanup of stale or merged Git worktrees. It automatically identifies and safely removes merged branches, calculates precise disk usage per worktree, and provides an interactive review process for unmerged or protected branches. Essential for maintaining clean repository environments.

This skill generates complete, deploy-ready static landing pages by analyzing a source code repository. It reads key files (README.md, CHANGELOG.md, etc.), extracts structured content (features, installation guides, FAQ), and compiles it into a professional, responsive HTML/CSS/JS site. Ideal for standardizing open-source project showcases, converting technical documentation into marketing pages, or quickly building a project homepage.